Middle Class Precariat: The Obsolescence of the Intelligent Workforce

Is your job safe? Are you sure? In recent times, journalists around the world are facing mass layoffs in the wake of the generative AI boom. Following Buzzfeed’s lead, even traditional new organisations like Murdoch’s News Corp are using AI to mass produce their content. 

To some, this widespread cull of the journalistic class in traditional media is a necessary casualty in the march to the Singularity. If AI can do the job at 70% of the quality but 1% of the cost, then for any media CEO, it makes sense. Machines don’t go on strike, they don’t require breaks, and they never go home after a hard day at the office. 

Modern content and consumption habits are increasingly formulaic. Ad-driven sites spurn quality in favour of clickbait dopamine, driving communication to become ever more bitesize – and become something a computer program can handle. With language models among the first neural networks to make a breakthrough, the writers were among the first in front of the robot firing squad. Yet as generative AI develops, they won’t be the last.

Just The Latest Panic?

Technology is a labour-saving device, and the efficiency savings should, in theory, lead to a more wealthy, more liberated society. If we can get technology to drastically save time and effort on essential activities, then – theoretically – everyone should have more free time, more leisure, and more opportunity to create wealth or art on their own terms. 

They said that about the plough, they said it about washing machines, neither which turned out to be wholly true. But they absolutely didn’t say it about industrial looms, or automobile production. ‘Once a generation we have a near panic [that] technology is destroying jobs’, says Professor Richard Cooper, and he’s right. Historically though, new jobs emerged in the vacated space. 

Is AI just the latest panic? This time, the fear is different. A general intelligence won’t just take over one field of work, but all of them. Generative AI is the most generalist labour-saving technology ever conceived. The annihilation of the content journalist class is only the beginning. First they came from the writers. Then they came for the graphic designers. Then they come for you.

The Two Paths 

So which is it? Will AI finally unlock an abundant life of leisure, or consign humanity to a new serfdom? Where is our Neo-Luddite movement? There are two paths. One, where AI just augments current jobs, piloted by skilled humans, boosting efficiency and output, leading to broad wealth creation, or even unlocking new talent where before the barriers to entry were too high. A virtuoso game designer who was never able to code well may suddenly find their visions easy to enact. This path requires an orderly, fair, consultative transition about the integration of AI agents into our economic workforce.

Capitalism is rarely that careful. The key aspect of this economic meteor is how AI agents may take over large areas of the labour force in one short, brutal blow. If it’s just the graphic designers who lose out, perhaps they can retrain. But if 25% or 50% of middle class jobs get obliterated in one fell swoop? The potential stress on society could lead to far more than widespread poverty, it could lead to revolution. Society exists based on a treaty between the have and the have-nots, a line constantly fought over in politics and, at times of strife, the battlefield. If huge parts of society suddenly become ‘useless’ to the political and social economy, it may not be them who have to change, but society itself; such change rarely happens without violence or upheaval.

Credit: Tesfu Assefa

An ‘Organic’ Tariff

There is hope. We may see a turn back to ‘organic’ work taking on its own value-add, the same way that homespun crafted products often fetch a higher price than factory-made products. Yes, an AI may produce superior, more complex, and more technically adept work at any given task, but it may lack that ‘human’ touch. Right now, with the current state of AI, this unheimlich, or uncanny, valley is quite easy to spot, and often induces aversion in observers. 

Over time, it may become ever more imperceptible. In the case of sectors firmly in the crosshairs, like clerical work, it never mattered in the first place. Yet the hope of an artisan society, an economy powered by human creativity and in which AI allows us to meet our basic needs while we focus on what makes us happy and fulfilled, is too utopian a view in a world where the processing power that fuels AI agents (and the code that runs them) is in the clutches of a few corporations.

Things Will Fall Apart Fast

AI needs to benefit all of us. To do that, we all need a stake in it. If we let our rapacious capitalist tendencies as a society run too long without safeguards on the development of AI – we may find wealth inequality, aided and abetted by AI agents working for zaibatsus, becomes too extreme too quickly to fix. We are sleepwalking toward a nightmare society, too enthralled by the promethean fire to notice that it’s burning everything.

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The Rise of AI Cryptocurrencies: How Machine Learning is Reshaping The Crypto Industry

Artificial Intelligence (AI) tools like OpenAI, and blockchain-powered networks like Ethereum have shaped the first few years of the 2020s, leveraging the power of Big Data, decentralized computing and network effects to disrupt a multitude of industries and reshape economic, social, and even environmental issues for better or worse.

The cryptocurrency revolution aims to transform finance through blockchain technology. Now, artificial intelligence (AI) is supercharging crypto with sophisticated machine learning algorithms. 

Where AI and blockchain intersect, they unlock a new wealth of possibilities for users, bolstered by AI’s productivity gains, blockchain’s security and its transparent and immutable participation trophies of cryptocurrency and non-fungible tokens (NFTs).

The appeal is easy to understand: AI offers real solutions to major challenges like security, scalability, and accessibility. And the industry is taking note, with more and more blockchain projects appearing that integrate machine learning into their DNA. 

This new breed of AI cryptocurrencies are rising from the wasteland of 2022’s crypto bear market to leverage AI for optimized transactions, predictive analytics, automated trading, and more. 

So the big question is, can AI-enhanced digital assets really unlock crypto’s true capabilities? Or will artificial intelligence’s data privacy issues drag virtual assets down with it to regulatory purgatory? Let’s check what all the hype’s about.

What Are AI Cryptocurrencies? 

AI cryptocurrencies are tokens that power AI-related blockchain platforms such as The Graph (the biggest AI crypto by market cap) and SingularityNET, arguably the most high-profile AI crypto project. 

In most cases, these tokens serve either as a means of payment for transactions, or as rewards for participants on the AI platform, or as a way of giving governance rights to holders. 

It’s important to note that not all cryptocurrency or blockchain projects which use AI in their systems have a token. 

How AI Cryptos Work

AI cryptocurrency projects use machine learning algorithms to make core crypto features smarter. They sift through huge datasets to offer a more personalized and improved user experience.

These AI coins are special types of crypto assets. They use artificial intelligence to make things better for everyone – whether it’s making your user experience smoother, scaling up the network, or tightening security.

And it’s not just about enhancing existing features; these coins are fueling new kinds of AI-focused projects. From decentralized marketplaces like SingularityNET to future market predictions and even managing your crypto portfolio like SingularityDAO, these AI coins are here to transform every inch of the digital financial landscape. Who and how will be addressed in a later article in our Crypto AI series. 

The Top Five AI Cryptocurrency Projects in 2023

You want names? OK OK. Here are five cool crypto projects that are leveraging artificial intelligence right now. We’ll cover more in our next article. 

  1. SingularityNET (AGIX) 

Founded by well-known AI researcher Ben Goertzel, SingularityNET is a decentralized AI-focused blockchain that allows anyone to monetize or utilize AI services. In its own words it’s building the next generation of decentralized AI and its network is powered by its AGIX token. SingularityNET has a blossoming ecosystem of partners and supported projects, such as Cardano and (yours truly) Mindplex

  1. Fetch.ai (FET) 

Fetch.ai is building an AI-powered blockchain to enable autonomous smart infrastructure. The open-access decentralized network allows devices to transact and share data via AI agents, with use cases across smart cities, supply chains, healthcare, and more. 

  1. Numerai (NMR)

Numerai is playing a numbers game, as its name suggests. It crowdsources machine learning for stock market predictions, and encrypts and anonymizes datasets to organize data science competitions among its community of data scientists. Winners are rewarded in NMR tokens based on the accuracy and predictive power of their models.

  1. Matrix AI Network (MAN) 

Matrix AI Network leverages AI to optimize blockchain architecture. The Intelligent Contracts and Intelligent Services chains allow smart contracts and machine learning models to interact seamlessly.

  1. Ocean Protocol (OCEAN)

This project focuses on data sharing, aiming to make datasets available for AI development without compromising on privacy. 

Benefits and Challenges of AI Cryptocurrencies 

Sorry Bitcoin: AI-injected digital assets deliver many advantages over traditional cryptocurrencies. Such as: 

They’re more efficient 

By automating manual processes, AI reduces costs and errors. Through the use of smart contracts, users also eliminate intermediaries, reducing another source of friction.

They’re more secure 

AI algorithms provide adaptive defense, and better threat detection against increasingly sophisticated cyberattacks. 

They can be personalized

AI analyzes trends and patterns to tailor solutions to each user. This provides a better customer experience.

They’re faster and more scalable 

AI optimizes protocols and transactions, increasing throughput, which translates to faster payments and high network capacity.

It’s not all a case of OK Computer though.

What are the biggest challenges for AI cryptos? 

Complexity and Cost

Sophisticated AI models require advanced expertise and resources, which many of today’s crypto projects, hamstrung by a long bear market, have in short supply. 

Data Privacy 

AI’s lifeblood is abundant user data. With Web2’s previous data exploits still fresh in the mind of consumers and regulators, this raises ethical concerns around consent and surveillance. And scanning people’s eyeballs isn’t providing good optics either, so to speak.

Energy Use

Training complex machine learning models uses a lot of computing power, which is a big no-no nowadays. Couple this with the general misconceptions over Bitcoin’s proof-of-work footprint, and it’s not a good look, even if most DeFi chains are environmentally-friendly proof-of-stake chains. 

Regulation

Laws have not kept pace with the rapid pace of AI and crypto development. Legislation for AI and crypto is in the pipeline that could put the brakes on the growth of both sectors. 

Credit: Tesfu Assefa

How is AI applied in Crypto? 

Let’s now look at some of the most popular current trends of utilizing AI in crypto:

AI in Decentralized Finance (DeFi) 

  1. Automated Crypto Trading 

As we covered in a previous article, AI-powered crypto trading bots have risen to prominence in 2023 due to their ability to automate the buying and selling of trading and investment positions based on technical indicators. 

AI bots can analyze market data, identify trends, and execute trades faster (sniping) and more efficiently than humans. Recently a Cointelegraph journalist took on an AI bot in a trading competition and lost

  1. Predictive Analytics

AI analyzes historical patterns in crypto prices, demand, and volatility. This powers price forecasting and predictive investment algorithms.

  1. Security 

AI algorithms can detect anomalies and cyberthreats. Then they adapt cyberdefenses, like in Numerai’s cryptographic security protocol.

  1. AI-driven DAOs: 

AI tokens are already used to fuel decentralized autonomous organizations (DAOs) and their applications, such as AI-powered trading algorithms and decentralized AI marketplaces. AI tools can optimize and speed up many DAO tasks, such as making proposals, summarizing governance decisions, transferring assets, and attracting new members.

  1. Fraud Detection

By learning normal user behavior patterns, AI can identify suspicious activities like ransomware attacks, hacking, and money laundering.

  1. Transaction Optimization 

AI can fine-tune transactions and protocols to enhance speed, cost, scalability, privacy, and other parameters.

  1. Personalization 

Analyzing user data allows AI cryptocurrencies to offer curated, tailored recommendations on investments, trades, and DeFi applications.

AI in Crypto Mining

AI presents solutions to enhance mining processes by improving algorithms, offering real-time data insights, and suggesting advanced hardware. Crypto mining uses powerful computational resources and specialized hardware to solve complex mathematical problems – whereas AI has a different set of hardware requirements.

Future Trends of AI in Crypto

Looking ahead, AI will likely evolve in tandem with blockchain infrastructure and aid its growth.

Here are four emerging trends:

AI-powered DeFi: Personalized and Efficient

DeFi is no longer just about simple transactions. With AI on board, DeFi are now your personal financial advisors, offering automated trading, advanced credit assessments, and tailor-made recommendations. 

AI Oracles: Bridging Real and Digital Worlds

AI Oracles go beyond regular data feeds; they intelligently enable AI systems to bring real-world data into smart contracts, bridging the gap between crypto and the real world.

Autonomous Agents: The Smart Brokers

Think of AI agents as your switched-on personal financial planners. They represent you in DeFi transactions, adapting to market changes and aiming to boost your returns.

Embedded AI: The Evolution Ahead

In the future, AI won’t just be an add-on; it’ll be part of the blockchain’s DNA. Embedded AI will perform a myriad of tasks such as improving transaction validation and enhancing security.

Endnote

While AI has taken a lot of limelight and lucre away from blockchain and crypto since its explosive rise in 2023, it should be viewed as a long-term ally that compliments instead of competes against digital asset technology. Its convergence with blockchain technologies has given rise to numerous promising AI crypto projects that will thrive over the coming decade. 

The benefits are easy to see: machine learning can make blockchains faster, cheaper, and more accessible, while AI cryptocurrencies are poised for mass adoption as the technology improves. 

Harnessing AI’s potential while addressing ethical concerns will be critical in democratizing DeFi and Web3’s realms. If that balance can be met, AI can transform crypto as limitlessly as it can transform other fields.

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A.I. in the Newsroom

Goodbye to the Byline? How A.I. May Change Authorship in News

In the world of print journalism, a byline is a coveted commodity. For journalists, it’s recognition of the hard work that goes into developing and writing a solid story. It’s no secret that reporters rely on editors, fact checkers, proofreaders, and automated spelling and grammar programs  for support in producing articles – that’s part of the process. 

But what happens when reporters use Artificial Intelligence (A.I.) to do more – such as produce paragraphs of content for their stories? Will reporters and news outlets disclose what is being produced by machines versus humans? Should the byline change to acknowledge A.I. generated content? 

A.I. Makes Inroads in the Newsrooms

Much has been written recently about the ability of machines and software programs to generate news articles. Tools such as QuillBot, ChatGPT and dozens more can create or paraphrase content. Many print and digital news organizations, faced with economic realities in today’s marketplace, have been quick to adopt A.I. 

News outlets have acknowledged the use of A.I. to generate (non-bylined) stores. The Associated Press states it was among the first news organizations to use AI in the newsroom: “Today, we use machine learning along key points in our value chain, including gathering, producing and distributing the news.”

“Roughly a third of the content published by Bloomberg News uses some form of automated technology,” The New York Times said in its 2019 article, “The Rise of the Robot Reporter.”

And in July, The New York Times reported that Google was testing a new tool called “Genesis” that generates news stories. “Google is testing a product that uses artificial intelligence technology to produce news stories, pitching it to news organizations including The New York Times, The Washington Post and The Wall Street Journal’s owner, News Corp, according to three people familiar with the matter.” 

As A.I. tools continue to be explored and adopted by reporters and the news media, some organizations have been sounding the alarm about the overall impact on the quality of newswriting and reporting created by automated systems. Inaccurate data, bias, and plagiarism – which have happened in human-generated stories – have also been uncovered in A.I. generated content.  

The most recent example of A.I. gone awry in a newsroom occurred last year at CNET. The news outlet issued corrections to more than half of 70 articles created by A.I. for its Money section. The articles, including many “how to” stories, were plagued by inaccuracies and plagiarism.

After correcting the articles, CNET announced it was changing its policies on the use of A.I. in generating news.

“When you read a story on CNET, you should know how it was created,” said Connie Guglielmo, former CNET Editor in Chief in her January 25 blog post. “We changed the byline for articles compiled with the AI engine to “CNET Money” and moved the disclosure so you don’t need to hover over the byline to see it. The disclosure clearly says the story was created in part with our AI engine. Because every one of our articles is reviewed and modified by a human editor, the editor also shares a co-byline. To offer even more transparency, CNET started adding a note in AI-related stories written by our beat reporters letting readers know that we’re a publisher using the tech we’re writing about.” 

(Guglielmo took on a new role in CNET following the A.I. debacle. She is now senior vice president on A.I. strategy.)

Many credible news outlets are letting readers know they are aware of the potential for A.I generated text to include bias and what actions they are taking to avoid it.

“We will guard against the dangers of bias embedded within generative tools and their underlying training sets,” The Guardian’s editor US Editor Betsy Reed states. “If we wish to include significant elements generated by AI in a piece of work, we will only do so with clear evidence of a specific benefit, human oversight, and the explicit permission of a senior editor. We will be open with our readers when we do this.”

Just last week, the Associated Press issued new guidance for use of A.I. in developing stories. “Generative AI has the ability to create text, images, audio and video on command, but isn’t yet fully capable of distinguishing between fact and fiction,” AP advises.

“As a result, AP said material produced by artificial intelligence should be vetted carefully, just like material from any other news source. Similarly, AP said a photo, video or audio segment generated by AI should not be used, unless the altered material is itself the subject of a story.”

Credit: Tesfu Assefa

Use of A.I. as a Tool, Not a Replacement for Human-Generated News

In some ways, the failed experiment at CNET supports the use of A.I. as a compliment to human reporting. Proponents cite the ability of A.I. to take the burden of mundane tasks off reporters and editors, increasing productivity and freeing up time to do what humans do best.

“Social Perceptiveness, Originality, and Persuasion” are cited as the human qualities that would be difficult for A.I. to replicate in newswriting and reporting, according to the website calculator “Will Robots Take My Job.” (Journalists are shown to be at a “Moderate Risk” of 47% of losing their jobs to automation, the site said.)

The new Google tool is designed to do just that, a company spokesperson said to the news outlet Voice of America.

“Our goal is to give journalists the choice of using these emerging technologies in a way that enhances their work and productivity,” the spokesperson said. “Quite simply these tools are not intended to, and cannot, replace the essential role journalists have in reporting, creating and fact-checking their articles.”

That philosophy may sit well with readers, as shown by a recent Pew Research Poll. When asked if A.I. in the newsroom was a major advance for the media, many didn’t see the value.

“Among Americans who have heard about AI programs that can write news articles – a use closely connected with platforms such as ChatGPT – a relatively small share (16%) describe this as a major advance for the news media, while 28% call it a minor advance. The largest share (45%) say it is not an advance at all,” the survey said.

Will Today’s Byline Become Extinct?

As A.I. becomes mainstreamed into the print reporting world, news outlets are faced with choices on how to acknowledge the origins of their content. Will reporters who use A.I. text in their stories acknowledge its source in their byline (‘By York Smith, and Genesis’)? Will they add a credit line at the end of the article? Or will A.I. generated sentences be considered just another tool in the hands of reporters and editors? 

A definitive answer may not be available yet. But credible news outlets that maintain the value of transparency will help the media develop a new industry standard in the world of machine learning.

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Old Money, New Game: Does Institutional Money Spell the End of Web3?

Big money – smart, dumb, and everything in between – is coming to Web3. The increasingly likely prospect of a spot Bitcoin ETF is a milestone in crypto’s final acceptance by the mainstream. Adoption is coming: a word that fuels the dreams of bedroom miners who have for years waited for the wider world to catch on to crypto’s promise.

For many, adoption is something to be fervently wished for, the final ratification of crypto’s potential. For others, it spells the end of crypto’s status as an alternative asset class, a death knell for the underground financial resistance that crypto historically represented.

Bitcoin: Always an Alternative

Bitcoin’s creation was predicated on being an alternative to big money. The first block in the entire chain contains a cryptic jab at central banks: “The Times 03/Jan/2009 Chancellor on brink of second bailout for banks.” The most recent bull run, although powered by stimulus checks and everyone having too much time on their hands, was built on the belief that Bitcoin and cryptocurrencies can be a store of value – a trustless hedge against the rampant money printing of central banks with levers operated by shady politicos funded by corporations keen to see their share price rise. I’m not suggesting this narrative is true or false, but it certainly fed the meteoric rise in crypto asset prices in 2020 and 2021.

Fifteen years of 0% interest and quantitative easing have made everyone’s money mean less (and everyone’s ownership mean more). Crypto represented a resistance to this. Almost since its inception, crypto has been seen as a chance for the little guy to make it, for Millenials and Gen Z (who are far more likely to be invested in crypto) to overturn the Boomers’ hoarded wealth and have a chance at replicating the stable, successful accumulation of their forebears, for those operating outside the standard rails of society to hold, store, and gain wealth. To let les miserables get involved in playing the game.

What ETFs Will Do To Crypto

The Securities and Exchange Commission (SEC) former chair’s statement that a spot Bitcoin ETF is ‘inevitable’ is, to some, a cause for sadness as well as celebration. Make no mistake, a Bitcoin ETF will open the doors for institutional money to get into crypto. ETFs (exchange traded funds) are a gold standard for institutional investors. Let’s talk about the positives first.

An ETF is a regulated mutual fund, professionally managed, that pays out dividends to shareholders based on its basket of securities. Unlike mutual funds, ETFs can be listed on a stock exchange, and are freely fungible for other cash or stocks. Most crucially, ETFs are an investment instrument that would not break fiduciary responsibility for pension funds, hedge funds, public businesses, or any other large institution who wants to hold crypto on their balance sheet and be exposed to crypto’s upside.

Upsides could be enormous if, as expected upon ETF ratification, institutions begin piling into crypto, as a method of diversifying their massive portfolios. The ‘$15 Trillion earthquake’ has the potential to send crypto not just to the moon, but to Oort Cloud. What about this is sad at all? Won’t everyone benefit? Well, yes, those who hold crypto will financially benefit – a lot.

Credit: Tesfu Assefa

A Requiem For Web3

The sadness is perhaps more philosophical, less practical. They worry that on the grandest scale, the cat will be out of the bag. Old money – banks, institutions, pension funds, Wall Street – these will become the primary drivers of the crypto market once crypto ETFs go live. The fun underground culture of Discord announcement parties, acid-mediated 125× Binance longs, Pepe-meme punts on shitcoins, and community-led price action with groundswell social campaigning will be completely swamped by the ticker tape tapestry of Bloomberg-reading MBA suits pumping tsunamis of money around the market or letting an algorithm HFT for them. Crypto will no longer be an alternative asset class, but just an asset class: regulated, controlled, and milled by the ancient financial machine that plunders all our tomorrows.

A New Financial System For Everyone

The hope, of course, is that crypto actually presents the opportunity for a fundamental change to the old systems. Ethereum (itself the subject of an ETF application) has, through its programmable smart contracts, the potential to act as an alternative financial substrate – one that is decentralised, trustless, and censorship resistant. One that levels the playing field and lets everyone ‘play up, play up, and play the game.’ It won’t just be Old Money buying into these assets, but these assets will form a new foundation on which the financial world can thrive – one that is permissionless and (at least nominally) fair, governed by smart contracts and regulated by all. Old Money might be entering the new game, but at least this time everyone gets a chance to join in.

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Understanding EIP-4844: Ethereum’s Proto-Danksharding Upgrade for Layer-2s

Introduction

Ethereum is drawing closer to another upgrade in Q4 of 2023 which will have a transformative effect on its whole ecosystem.

The Cancun-Deneb (Or Dencun) upgrade will feature the important EIP-4844 protocol, designed to boost Ethereum’s competitiveness and the performance of its slew of layer-2 scaling chains.

Also known as Proto-Danksharding, in honor of two of its researchers, Proto Lambda and Dankrad Feist, EIP-4844 is a part of the broader Ethereum Improvement Proposal protocol, which allows for the introduction of new features to its network. 

It was conceived by Ethereum co-founder Vitalik Buterin (who recently shared his vision of three transitions needed to scale the network) along with a team of developers with the primary objective of lowering gas fees, particularly for layer-2 rollup solutions such as Optimism, Arbitrum, and zkSync Era, without compromising on the network’s decentralization. 

But what exactly is EIP-4844, and why is it so crucial for the future of Ethereum and the development of Web3? Let’s take a closer look. 

Sharding vs Danksharding vs Proto-danksharding

To fully grasp the impact of EIP-4844, it’s essential to understand what sharding and danksharding are. 

  • Sharding is a long-time end goal for Ethereum that dates back all the way to the 2018 Casper roadmap. It involves partitioning a blockchain network into smaller units, known as ‘shards,’ to improve transaction throughput and reduce network congestion. To get there though, some preliminary steps are needed.
  • Danksharding is a new architectural approach that relies on data blobs to scale the Ethereum blockchain. It’s a complex process that will be implemented in phases, with EIP-4844 serving as the initial step.
  • In the words of Vitalik Buterin, proto-danksharding provides the “scaffolding” for future sharding upgrades. It implements most of the logic required for danksharding without actually initiating sharding.

What is EIP-4844?

In short, EIP-4844, or Ethereum Improvement Proposal 4844, aims to enhance scalability by exponentially lowering gas fees on layer-2 rollups through innovative blob-carrying transactions. Yes, you read that correctly. 

Interestingly, EIP-4844 is a temporary fix – until sharding is fully supported on Ethereum and solves scaling. EIP-4844 introduces a new way to split transaction information, such as verification rules and transaction formats, without the need for full sharding.

What Are Shard Blob Transactions?

One of the most groundbreaking features of EIP-4844 is the introduction of a new transaction type known as “blob transactions”. These transactions allow for data blobs to be temporarily stored in the beacon node.

Blobs are essentially data packages around 125kB in size. Compared to regular transactions, blob transactions are cheaper to execute, but they are not accessible to the Ethereum Virtual Machine (EVM).

Scalability and Data Bandwidth

The data bandwidth for a slot in proto-danksharding is capped at 1 MB, a significant reduction from the previous 16 MB, which is a massive change aimed at alleviating Ethereum’s well-known scalability issues. The EIP-4844 update does not affect gas usage for standard Ethereum transactions.

Credit: Tesfu Assefa

Why is EIP-4844 A Game-Changer For Ethereum and L2s?

High gas fees have been a significant barrier to Ethereum’s mass adoption, as any DeFi user will tell you. People who tried to trade on Uniswap or flip NFTs during 2021s wild bull run (with its record-high ETH gas fees) can attest that some transactions cost hundreds of dollars in fees. Network fees on any blockchain can skyrocket when on-chain activity increases, making the network expensive and inaccessible for many users.

The advent of layer-2 side chains that use optimistic and zero-knowledge (ZK) rollup technology to compile transaction batches has done a lot to alleviate the pressure on Ethereum’s mainnet. The Optimism chain was presented in March 2022 by Proto Lambda with claims that it could potentially lower L2 transactions by up to 100x. But as things stand, when network usage and congestion soar, transactions still get unacceptably pricey.

EIP-4844 aims to be a game-changer by significantly reducing transaction fees and increasing throughput. Yet it’s only a stop-gap measure until the full implementation of data sharding, which would add around 16 MB per block of dedicated data space for rollups to use.

The Future of Ethereum and Rollups

With so much building happening on Ethereum due to its stable infrastructure and proven security, it’s no surprise that Buterin believes that the future of scaling the world’s first smart contract network will revolve around these rollup chains. Proto-danksharding is a pivotal stop on this roadmap. 

Post-implementation, users can expect faster transactions and lower fees, which will enhance Ethereum’s competitiveness in the blockchain sector, and help it to stretch its massive lead over rival layer-1s such as “ETH killers” like Solana, Cardano, and EVM-compatible chains such as Avalanche and BNB Smart Chain. These chains have also all been plagued with their own development setbacks from time to time. 

Conclusion

EIP-4844, or Proto-Danksharding, is more than just a not-so-catchy name; it’s a pivotal upgrade that promises to address some of Ethereum’s most pressing issues. From reducing layer-2 gas fees to paving the way for full sharding, this proposal is another worthy milestone on the road to Ethereum’s final state as the world’s computer.

The scheduled rollout in Q4 2023 should hopefully go through without any major surprises, if the network’s last few upgrades are anything to go by. Sailing was rarely smooth for any update prior to 2020’s Beacon Chain fork (2019’s Constantinople fracas comes to mind), but the ones after all breezed through with flying colors, giving ETH users and developers much-needed confidence. Let’s hope the Dencun update provides more of the same. 

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The Singularity Obsessed AI Hacker in Antero Alli’s Last Film Blue Fire is Only The Beginning

I suppose the way to get Mindplexians interested in Antero Alli – author, theater producer, experiential workshop leader and film director – is through his ties to Timothy Leary and Robert Anton Wilson starting back in the 1980s, where that pair were advocating transhumanist slogans like Space Migration, Intelligence Increase, Life Extension.

But the reality is that Alli has carved his own path as a writer, a thinker and director. And as he slowly exits corporeality, it’s his film oeuvre that most fascinates me.  

I recently spent a day watching several of his films and it struck me that I was looking at part of  an entire body of work that has been largely neglected by those writing about and advocating for indie films. Alli’s films may be about to be discovered. They certainly deserve substantial notice. There are hours of enjoyment and intrigue awaiting viewers.

And while enough of his films enclose neo-tech tropes like VR and AI to cause one or two commentators to toss out the buzzword “cyberpunk,” these are all ultimately human stories leaning on depth psychology, Jungian symbolism, dreams and real experience.

In the preview for his latest film (and most likely his last) ‘Blue Fire’, Alli highlights the Singularity.

The central protagonist is an underground singularity-obsessed AI hacker. Scenes show male computer-freak social awkwardness, unrequited male obsession with a woman and a bad Salvia Divinorum trip (been there). Ultimately ‘Blue Fire’ is not a film about AI or the personalities of underground hacker archetypes. It’s a film about human connections — connections made but mostly connections missed.

I interviewed Antero Alli by email.

R.U. Sirius: Since Mindplex readers probably aren’t familiar with your work, what would you say is the theme or project or search that runs through all of your work that includes books, theater, experiential workshops and film, including the most recent one we’re discussing today?

Antero Alli: The silver thread running through most everything I’ve put out to the public since 1975 – my books, films, theatre works, Paratheatrical experiments – reflects my ongoing fascination with how our diurnal earth-based realities are impacted in meaningful ways by our nocturnal dreams and related astral or out-of-body events. I have felt compelled to share these visions through the Art of words, images, and human relations. All this obsession started back in 1975 when I endured a spontaneous out-of-body experience at the age of 23. I say endured since the experience itself was traumatic and a massive shock to my concept of identity. I was no longer able, in all honesty, to identify as a physical body after being shown more truth when seeing and knowing myself as a light body, an electric body, cased within the physical body. No drugs were involved. The only condition I can relate it to was exhaustion from an intense theatre rehearsal that evening. All my films are oneiric docufictions, where real life experiences are camouflaged and spun by my feral poetic imagination.

Credit: Antero Alli

RUS: We met when we were both working and playing with the ideas of Timothy Leary and Robert Anton Wilson. To the extent that their ideas are likely of interest to the mostly technophile readers of Mindplex, they would be attracted to the technotopian ideas they advocated like SMI²LE and evolutionary brain circuits as opened by drugs and technology, and then Leary’s later advocacy of cyberpunk and the digital revolution. How do you see your own work in relationship to these tropes?

AA: My contribution to the legacies of Timothy Leary and Robert Anton Wilson is demonstrated through my thirty-year era of working with The Eight-Circuit Brain model. This started in 1985 with the publication of my first 8-circuit book, ‘Angel Tech’, updated and expanded in 2009 with ‘The Eight Circuit Brain: Navigational Strategies for the Energetic Body’. (Both books are still in print at The Original Falcon Press.) My approach is somatic and experience-oriented, rather than theoretical or philosophical. I relate the eight-circuit model as a diagnostic tool to track and identify multiple states of consciousness and eight functions of intelligence that can be accessed as direct experience through ritual, meditation, and trigger tasks. This embodiment bias sets my circuit work apart from Leary’s more theoretical approach and Wilson’s use of multiple systems theory to expand the eight-circuit playing field. Between the three of us, I think we cover the bases pretty well.

RUS: The dramatic persona in Blue Fire is an underground AI hacker… seemingly a singularitarian. How did you conceive of this character? Was he based on someone or a composite or a pure imagining?

AA: The AI-coder Sam, played by Bryan Smith, was inspired in part by the actor — a singular personality with a dynamic physical sensibility and this very pure kind of cerebral charisma, a complexity that I felt could brilliantly serve the film. I was also intrigued and inspired by the subculture of coders that I discovered talking with a few of my friends, AI freaks and serious hackers, who shall remain anonymous.

RUS: Without giving up too much of the plot, the other protagonists are a relatively normal nice seemingly-liberal couple. The dynamic between could be read as a contrast between neurotypicals and neuro-atypicals, In this case the atypical doesn’t do very well but is perhaps a catalyst for putting the typicals through some changes. Would you read it that way?

AA: The so-called typical couple are not lovers or married or in any kind of romantic involvement; nowhere in their dialogue mentions or indicates that. What is clear is that she is a student in the college-level Psychology 101 that he teaches. They form a bond over their shared interest in dreams, a bond that deepens into a troubling mentorship. All three characters act as catalysts for each other in different ways. Much of this starts in their nocturnal dreams and how their daily discourse is impacted by these dreams. This daytime-dreamtime continuum continues as a thread throughout most of my films.

RUS: Again, not giving up too much, the hacker dude smokes some salvia divinorum… and based on my own experiences, you got that right in the sense that it’s often an uncomfortable high. I’ve referred to it as “naggy”. People who want to be happy about being in disembodied cyberspace should probably make ketamine their drug of choice (I’m just chattering here but welcome you chattering back) or even LSD rather than a plant. McKenna used to believe that with plant psychedelics there’s someone or something in there… kind of another mind with something to impart to the imbiber. Any thoughts on this or thoughts on minds other than our own here on earth and what they can teach us?

AA: I knew Sam, the A.I. coder, had a drug habit, but didn’t know at first what drug would be the most indicative of this native state in mind. What drug would he gravitate towards? What drug amplifies his compartmentalizing, highly abstract, and dissociative mindset? After smoking salvia several times, it seemed like a good fit (not for me but for Sam). By the way, I don’t make my films to school the audience or teach them anything. It would be a mistake to also view any of the characters in my films as role models, unless your Ego Ideal includes flaws, shortcomings, and repressed Shadow material. Though ‘Blue Fire’ revolves around Sam’s AI coding, this is also not a story about AI but how AI acts on Sam’s psyche. Like my other films, I explore human stories planted in extreme circumstances or situations where people face and react to realities beyond their control or comprehension.


RUS: Aside from AI, virtual reality pops up in some of your work, and the language of hacking occurs here and there. But I don’t think your work would be categorized as cyberpunk or even sci-fi. What role would you say fringe tech and science play in your films?

AA: The fringes of tech and science play a role in those films – their presence amplifies the human story or shows the viewer a new context or way of seeing how the characters interact with tech and science. This keeps me and my films honest, as I’m no techie or science nerd. My deep background in theatre and ritual (Paratheatre) has slam-dunked me into the deeper subtext of human relations and how this interacts with the transpersonal realms of archetypes and dreams.

RUS: I’m feeling a little claustrophobic making what I suspect might be your last or one of your last interviews just about Blue Fire as directed at the Mindplex audience. If you’re up to it, why don’t you hit the world with your parting shot, so to speak. A coda? A blast of wisdom? A great fuck-all? A kiss goodbye? Whatever you feel. And thanks for being you.

AA: I’m feeling a bit claustrophobic about answering your question. I get that others sometimes think of me as this fount of wisdom – which humors me to no end. I suppose whatever ‘wisdom’ has been born in me, it’s come from making many mistakes and errors of judgment that I have felt compelled to correct as soon as possible, if only because I hate the dumbdown feeling of making the same mistake more than once. This self-correction process vanquished any existing fear of making mistakes, in lieu of an excitement for making new mistakes – defining my creative approach to most everything I do as experimental. Everything starts out as an experiment to test the validity of whatever idea, plan, or theory I start with. Sometimes I’m the boss and sometimes the situation is the boss.

No fuck alls, no kisses goodbye, no regrets. I remain eternally grateful to have lived an uncommonly fulfilling life by following and realizing my dreams. At 70, this has proven a great payoff during my personal end times (I was diagnosed with a terminal disease and don’t know my departure date).

BLUE FIRE Official site

https://www.verticalpool.com/bluefire.html

Antero Alli Films online

https://www.verticalpool.com/dvd.html

9/21 Portland premiere

Purchase Advance Tickets

Sept. 22 – YouTube Premiere

Sept. 26 – New York Premiere

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System Shocks: The Perils of Corporate AI

Do you want to be a paperclip? This isn’t a metaphor, rather a central thesis of Nick Bostrom’s harbinger book Superintelligence. In it, he warns of the calamity lurking behind poorly thought out boot up instructions to AI. An AI tasked with the rather innocuous goal of producing paperclips could, if left unchecked, end up turning every available mineral on earth into paperclips and, once completed, set up interstellar craft to distant worlds and begin homogenising the entire universe into convenient paper organisers.

Horrifying? Yes. Silly? Not as much as you may think. Bostrom’s thought experiment strikes directly at a core problem at the heart of machine learning. How do you appropriately set goals? How do you ensure your programming logic inexorably leads to human benefit? Our promethean efforts with AI fire is fraught with nightmare fancies, where a self-evolving, sentient machine takes its instructions a little too literally – or rewrites its failsafe out entirely. Skynet’s false solution is never too far away and – to be fair to literary thinkers, AI builders, and tech cognoscenti – we have always been conscientious of the problem, if not necessarily the solutions.

Learning Machines Require Resources

The thing is, machine learning is not easy to research. You need insane processing power, colossal datasets, and powerful logistics – all overseen by the brightest minds. The only entities with the unity of will to aggressively pursue AI research are the corporations, in particular the tech giants of Silicon Valley. Universities make pioneering efforts, but they are often funded by private as well as public grants, with their graduates served up the conveyor belt to the largest firms. In short, any advances in AI will likely come out of a corporate lab, and thus its ethical construction will be mainly undertaken in the pursuit of profit.

The potential issues are obvious. An advanced AI with access to the internet, poorly defined bounds, capital to deploy, and a single goal to advance profit for its progenitor organisation could get out of hand very quickly. A CEO, tasking it one evening, could wake up in the morning to find the AI has instigated widespread litigation against competitors and shorted bluechip stocks in their own sector at vast expense for a minor increase in balance sheet profit – that is a best case scenario. Worst case – well, you become a paperclip.

The Infinitely Destructive Pursuit of Profit 

Capitalism’s relentless profit incentive has been the cause of global social traumas the world over. From environmental desecration for cheaper drinking water, to power broking with user’s data staining politics, the general ruination of public services by rentier capitalists ransacking public infrastructure and pensions for fast profit is a fact. For sure, capitalism ‘works’ as a system – in its broadest conception, and yes, it does a great job of rewarding contribution and fostering innovation. Yet we all know the flaw. That single, oppressive focus on ever increasing profit margins in every aspect of our lives eventually leads to a race to the bottom for human welfare, and hideous wealth inequality as those who own the means of production hoard more and more of the wealth. When they do, social chaos is never far behind. The way that capitalism distorts and bends from its original competition-focused improvement into a twisted game of wealth extraction is just a shadow of what would occur if an AI takes the single premise of profit and extrapolates the graph to infinity. Corporate entities may not be the proper custodians of the most powerful technologies we may ever conceive, technologies that may rewrite society to their own ends.

Credit: Tesfu Assefa

A Likely Hegemony; Eternal Inequality

This may sound like extreme sci-fi fear mongering. A tech junkie’s seance with the apocalypse. So let’s consider a more mundane case – whoever has AI has an unassailable competitive advantage that, in turn, gives them power. Bard, ChatGPT, and Bing are chatbots, but there are companies who are working on sophisticated, command and control AI technologies. AIs that can trawl CCTV databases with facial recognition. AIs that can snapshot credit and data of an individual to produce a verdict. AIs that can fight legal cases for you. AIs that can fight wars. The new means of production in a digital age, new weapons for the war in cyberspace, controlled by tech scions in glass skyscrapers.

If these AIs are all proprietary, locked in chrome vaults, then certain entities will have unique control over aspects of our society, and a direct motive to maintain their advantage. Corporate AIs without checks and balances can and will be involved in a shadow proxy war. For our data, our information, and our attention. It’s already happening now with algorithms. Wait until those algorithms can ‘think’ and ‘change’ (even if you disallow them a claim to sentience) without management’s approval. It won’t be long before one goes too far. Resources like processing power, data, and hardware will be the oil of the information age, with nation states diminished in the face of their powerful corporations. A global chaebol with unlimited reach in cyberspace. Extreme inequality entrenched for eternity.

The Need for Open-Source AI

There is an essential need, therefore, for open-source access to AI infrastructure. Right now, the open-source AI boom is built on Big Tech handouts. Innovation around AI could suffer dramatically if large companies rescind access to their models, datasets and resources. They may even be mandated too by nation states wary of rival actors stealing advances to corrupt them to nefarious ends. 

Yet just as likely, they will do so afraid of losing their competitive advantage. When they do, they alone may be the architects of the future AIs that control our daily lives – with poorly calibrated incentives that lack social conscience. We’ve all seen what happens when a large system’s bureaucracy flies in the face of common sense, requiring costly and inefficient human intervention to avert. What happens when that complex system is the CEO, and its decisions are final? We’ve seen countless literary representations, from GlaDos to Neuromancer’s Wintermute to SHODAN, of corporate AIs run amok – their prestige access to the world’s data systems, the fuel for their maniacal planning. When the singularity is born, whoever is gathered around the cradle will ordain the future. Let’s all be part of the conversation. 

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Digital Title Deeds: Ownership for a Virtual Generation or Commodified Engagement?

NFTs are, by now, old news. No single aspect of crypto has been more derided than the ‘million dollar jpegs’ which headlined the last crypto bullrun. Around coffee tables, bars, and Discords all over the world, snide remarks about the utter insanity of the modern market reigned supreme. To many, the idea that a duplicable image of an Ape could set you up for life was cause for bemusement, anger, and not the least bit of jealousy. 

Has this modern speculative capitalism gone mad? Was it the outrageous excess of the crypto-minted tech bros’ 1% indulging themselves in the new ‘roaring 20s’ of the 21st century amid a backdrop of pandemic and war? Or was someone, somewhere, actually on to something: that the dizzying prices and speculative excess was a harbinger of a newly consecrated form of online ownership and digital demesnes that would lead to a new concept of cyberspace.

The answer, of course, is that all three are true. Though the positive narrative has, to date, almost been entirely sunk by the precipitous, and in some cases hilarious, losses that early NFT ‘investors’ suffered. All gold rushes bring charlatans, and nowhere was this more acute in the insane pell mell towards the jackpot that occurred as literally anyone with a few thousands dollars and a basic concept of programming, blockchain or otherwise, could spin up a brand new NFT collection, promising insane gains, ambitious roadmaps, and eternal friendship among the community. The barrier to entry was near-zero, and the market was hungry for every new ape collection that rolled off the bedroom CEO production line. A lot of people – mainly the young – made a lot of money.

Everyone else lost everything. Very few projects ever grew beyond the initial launch. Leaders collected the minting fees and promptly stopped working, realising perhaps innocently, perhaps not, that the roadmaps they had set out would be difficult even for Apple to execute in the timeframes spoken about. Discords turned feral as thousands of users realised a 14 year old, perfectly innocently, had sold them a few pictures of whales to test his skills with Rust, with zero plans to do anything else for the project. It was just a hobby to make a few dollars. 

Credit: Tesfu Assefa

Yet even without a roadmap, communities wrote one in their heads. This was going to be the latest craze, the keys to a better virtual future where whale-owners would walk tall in the new halls of cyberspace, a chance to pay off the mortgage. How dare this 14 year old kid rob us of that future they’d already dreamed they were in. Scammer, I can doxx you! I know where you live!

How did this happen? What is it about those jpeg apes that so seized the cultural imagination? Yes, there were an incredible amount of push factors – Covid, quantitative easing, stimulus, lockdown, BTC’s massive gains creating crypto-related mania. But there must have been more – what was the pull?

First, they’re not jpegs. The picture associated with an NFT is not truly the NFT itself. An NFT is a token created (‘minted’) by a smart contract that has certain information on it (like pointing to a webhost hosting a jpeg), is completely unique (even if duplicates are made, each NFT would still a specific blockchain signature), and has an owner ascribed to it (usually the person sending tokens to the smart contract to make it execute its creation function. The NFT’s information, the transaction that created it, and the current ownership is all publicly visible, irrefutable, and benefits its blockchain’s security, making fraud impossible without breaking the network entirely.

This means that we’d finally figured out a way to record digital ownership, and thus digital items, which due to their reproducibility had very little worth, but could suddenly have a lot. It started with art, but games quickly realised they could consecrate ownership over their in-game assets to players, creating cooperative gaming experiences. Ownership of the first digital ‘printing’ of your favourite artist’s new album having kudos. The ability for vibrant secondary economies to spring up around their favourite talent as users could trade NFTs with one another, or sell them. NFTs created a whole new economy to be exploited where there was none before. And boy, was it exploited. Influencers, artists, and anyone with a following could create new engagement models using NFTs, with bespoke experiences attached. At time of writing, Cristiano Ronaldo’s instagram bio asks his 600m followers to join him on his NFT journey, and bid for NFTs in open auction for a chance to meet the man himself.

What’s wrong with a ticket though? Just tell me why an ape picture is worth millions. Well, the reason is, as with so many new technologies, is the possibilities. Bitcoin, Ethereum, Solana, Cosmos – whichever – blockchains by their nature are designed to be permanent, digitally-native operating systems for our future. An NFT bought in 2017 will keep its functionality for eternity. It can’t be erased from the blockchain, or from time. 

That means that should, in the future, a new business, say, declare that the only way to buy the first release of their hot new product is by owning said NFT, it would be easy for them to borrow the operation security of the blockchain and create instant exclusive access to whatever ‘club’ of people they those at near-zero outreach cost. Membership of said clubs would be powerful, digital cartels impossible to access except through the NFT and the key it provides. Or a blockchain game grows and develops a powerful online community over a decade. The first NFTs of in-game assets would be priceless, and nothing would stop developers engineering new functionality for them over time. Only a fool would suggest that we are not becoming ever more cyberised as history advances, so why wouldn’t the first digital artefacts – the first time we can truly declare failsafe ownership of a digital asset – have value? 

As alluded to, all of that is decades hence. NFTs have been mooted for use in retail, supply chains, schools but, as ever, the integrative technology to make that happen and make it useful has a long way to go. Those most in the know are too busy getting rich, or at least were, to truly focus on advancing NFTs as a useful digital technology. Now, as almost every project suffers on the wind-down from mania, perhaps it’s time to take stock of what digital ownership could truly give us. As a blaze of stimuli, images, and simulacra race past us in virtual headsets, NFTs just give us something to hold on to.

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The Astonishing Vastness of Mind Space: The incalculable challenges of coexisting with radically alien AI superintelligence

More things in heaven and earth

As humans, we tend to compare other intelligences to our own, human, intelligence. That’s an understandable bias, but it could be disastrous.

Rather than our analysis being human-bound, we need to heed the words of Shakespeare’s Hamlet:

There are more things in heaven and earth, Horatio, than are dreamt of in our philosophy.

More recent writers, in effect amplifying Shakespeare’s warning, have enthralled us with their depictions of numerous creatures with bewildering mental attributes. The pages of science fiction can, indeed, stretch our imagination in remarkable ways. But these narratives are easy to dismiss as being “just” science fiction.

That’s why my own narrative, in this article, circles back to an analysis that featured in my previous Mindplex article, Bursting out of confinement. The analysis in question is the famous – or should I say infamous “Simulation Argument”. The Simulation Argument raises some disturbing possibilities about non-human intelligence. Many critics try to dismiss these possibilities – waving them away as “pseudoscience” or, again, as “just science fiction” – but they’re being overly hasty. My conclusion is that, as we collectively decide how to design next generation AI systems, we ought to carefully ponder these possibilities.

In short, what we need to contemplate is the astonishing vastness of the space of all possible minds. These minds vary in unfathomable ways not only in how they think but also in what they think about and care about.

Hamlet’s warning can be restated:

There are more types of superintelligence in mind space, Horatio, than are dreamt of in our philosophy.

By the way, don’t worry if you’ve not yet read my previous Mindplex article. Whilst these two articles add up to a larger picture, they are independent of each other.

How alien?

As I said: we humans tend to compare other intelligences to our own, human, intelligence. Therefore, we tend to expect that AI superintelligence, when it emerges, will sit on some broad spectrum that extends from the intelligence of amoebae and ants through that of mice and monkeys to that of humans and beyond.

When pushed, we may concede that AI superintelligence is likely to have some characteristics we would describe as alien.

In a simple equation, overall human intelligence (HI) might be viewed as a combination of multiple different kinds of intelligence (I1, I2, …), such as spatial intelligence, musical intelligence, mathematical intelligence, linguistic intelligence, interpersonal intelligence, and so on:

HI = I1 + I2 + … + In

In that conception, AI superintelligence (ASI) is a compound magnification (m1, m2, …) of these various capabilities, with a bit of “alien extra” (X) tacked on at the end:

ASI = m1*I1 + m2*I2 + … + mn*In + X

What’s at issue is whether the ASI is dominated by the first terms in this expression, or by the unknown X present at the end.

Whether some form of humans will thrive in a coexistence with ASI will depend on how alien that superintelligence is.

Perhaps the ASI will provide a safe, secure environment, in which we humans can carry out our human activities to our hearts’ content. Perhaps the ASI will augment us, uplift us, or even allow us to merge with it, so that we retain what we see as the best of our current human characteristics, whilst leaving behind various unfortunate hangovers from our prior evolutionary trajectory. But that all depends on factors that it’s challenging to assess:

  • How much “common cause” the ASI will feel toward humans
  • Whether any initial feeling of common cause will dissipate as the ASI self-improves
  • To what extent new X factors could alter considerations in ways that we have not begun to consider.

Four responses to the X possibility

Our inability to foresee the implications of unknowable new ‘X’ capabilities in ASI should make us pause for thought. That inability was what prompted author and mathematics professor Vernor Vinge to develop in 1983 his version of the notion of “Singularity”. To summarize what I covered in more detail in a previous Mindplex article, “Untangling the confusion”, Vinge predicted that a new world was about to emerge that “will pass far beyond our understanding”:

We are at the point of accelerating the evolution of intelligence itself… We will soon create intelligences greater than our own. When this happens, human history will have reached a kind of singularity, an intellectual transition as impenetrable as the knotted space-time at the center of a black hole, and the world will pass far beyond our understanding. This singularity, I believe, already haunts a number of science fiction writers. It makes realistic extrapolation to an interstellar future impossible.

Reactions to this potential unpredictability can be split into four groups of thought:

  1. Dismissal: A denial of the possibility of ASI. Thankfully, this reaction has become much less common recently.
  2. Fatalism: Since we cannot anticipate what surprise new ‘X’ features may be possessed by an ASI, it’s a waste of time to speculate about them or to worry about them. What will be, will be. Who are we humans to think we can subvert the next step in cosmic evolution?
  3. Optimism: There’s no point in being overcome with doom and gloom. Let’s convince ourselves to feel lucky. Humanity has had a good run so far, and if we extrapolate that history beyond the singularity, we can hope to have an even better run in the future.
  4. Activism: Rather than rolling the dice, we should proactively alter the environment in which new generations of AI are being developed, to reduce the risks of any surprise ‘X’ features emerging that would overwhelm our abilities to retain control.

I place myself squarely in the activist camp, and I’m happy to adopt the description of “Singularity Activist”.

To be clear, this doesn’t mean I’m blind to the potential huge upsides to beneficial ASI. It’s just that I’m aware, as well, of major risks en route to that potential future.

A journey through a complicated landscape

As an analogy, consider a journey through a complicated landscape:

Credit: David Wood (Image by Midjourney)

In this journey, we see a wonderful existential opportunity ahead – a lush valley, fertile lands, and gleaming mountain peaks soaring upward to a transcendent realm. But in front of that opportunity is a river of uncertainty, bordered by a swamp of ambiguity, perhaps occupied by hungry predators lurking in shadows.

Are there just two options?

  1. We are intimidated by the possible dangers ahead, and decide not to travel any further
  2. We fixate on the gleaming mountain peaks, and rush on regardless, belittling anyone who warns of piranhas, treacherous river currents, alligators, potential mud slides, and so on

Isn’t there a third option? To take the time to gain a better understanding of the lie of the land ahead. Perhaps there’s a spot, to one side, where it will be easier to cross the river. A location where a stable bridge can be built. Perhaps we could even build a helicopter that can assist us over the strongest currents…

It’s the same with the landscape of our journey towards the sustainable superabundance that could be achieved, with the assistance of advanced AI, provided we act wisely. That’s the vision of Singularity Activism.

Obstacles to Singularity Activism

The Singularity Activist outlook faces two main obstacles.

The first obstacle is the perception that there’s nothing we humans can usefully do, to meaningfully alter the course of development of ASI. If we slow down our own efforts, in order to apply more resources in the short term on questions of safety and reliability, it just makes it more likely that another group of people – probably people with fewer moral qualms than us – will rush ahead and create ASI.

In this line of thinking, the best way forward is to create prototype ASI systems as soon as possible, and then to use these systems to help design and evolve better ASI systems, so that everyone can benefit from what will hopefully be a wonderful outcome.

The second obstacle is the perception that there’s nothing we humans particularly need to do, to avoid the risks of adverse outcomes, since these risks are pretty small in any case. Just as we don’t over-agonise about the risks of us being struck by debris falling from an overhead airplane, we shouldn’t over-agonise about the risks of bad consequences of ASI.

Credit: David Wood

But on this occasion, where I want to focus is assessing the scale and magnitude of the risk that we are facing, if we move forward with overconfidence and inattention. That is, I want to challenge the second of the above misperceptions.

As a step toward that conclusion, it’s time to bring an ally to the table. That ally is the Simulation Argument. Buckle up!

Are we simulated?

The Simulation Argument puts a particular hypothesis on the table, known as the Simulation Hypothesis. That hypothesis proposes that we humans are mistaken about the ultimate nature of reality. What we consider to be “reality” is, in this hypothesis, a simulated (virtual) world, designed and operated by “simulators” who exist outside what we consider the entire universe.

It’s similar to interactions inside a computer game. As humans play these games, they encounter challenges and puzzles that need to be solved. Some of these challenges involve agents (characters) within the game – agents which appear to have some elements of autonomy and intelligence. These agents have been programmed into the game by the game’s designers. Depending on the type of game, the greater the intelligence of the built-in agents, the more enjoyable it is to play it.

Games are only one example of simulation. We can also consider simulations created as a kind of experiment. In this case, a designer may be motivated by curiosity: They may want to find out what would happen if such-and-such initial conditions were created. For example, if Archduke Ferdinand had escaped assassination in Sarajevo in June 1914, would the European powers still have blundered into something akin to World War One? Again, such simulations could contain numerous intelligent agents – potentially (as in the example just mentioned) many millions of such agents.

Consider reality from the point of view of such an agent. What these agents perceive inside their simulation is far from being the entirety of the universe as is known to the humans who operate the simulation. The laws of cause-and-effect within the simulation could deviate from the laws applicable in the outside world. Some events in the simulation that lack any explanation inside that world may be straightforwardly explained from the outside perspective: the human operator made such-and-such a decision, or altered a setting, or – in an extreme case – decided to reset or terminate the simulation. In other words, what is bewildering to the agent may make good sense to the author(s) of the simulation.

Now suppose that, as such agents become more intelligent, they also become self-aware. That brings us to the crux question: how can we know whether we humans are, likewise, agents in a simulation whose designers and operators exist beyond our direct perception? For example, we might be part of a simulation of world history in which Archduke Ferdinand was assassinated in Sarajevo in June 1914. Or we might be part of a simulation whose purpose far exceeds our own comprehension.

Indeed, if the human creative capability (HCC) to create simulations is expressed as a sum of different creative capabilities (CC1, CC2, …),

HCC = CC1 + CC2 + … + CCn

then the creative capability of a hypothetical superhuman simulation designer (SCC) might be expressed as a compound magnification (m1, m2, …) of these various capabilities, with a bit of “alien extra” (X) tacked on at the end:

SCC = m1*CC1 + m2*CC2 + … + mn*CCn + X

Weighing the numbers

Before assessing the possible scale and implications of the ‘X’ factor in that equation, there’s another set of numbers to consider. These numbers attempt to weigh up the distribution of self-aware intelligent agents. What proportion of that total set of agents are simulated, compared to those that are in “base reality”?

If we’re just counting intelligences, the conclusion is easy. Assuming there is no catastrophe that upends the progress of technology, then, over the course of all of history, there will likely be vastly more artificial (simulated) intelligences than beings who have base (non-simulated) intelligences. That’s because computing hardware is becoming more powerful and widespread.

There are already more “intelligent things” than humans connected to the Internet: the analysis firm Statista estimates that, in 2023, the first of these numbers is 15.14 billion, which is almost triple the second number (5.07 billion). In 2023, most of these “intelligent things” have intelligence far shallower than that of humans, but as time progresses, more and more intelligent agents of various sorts will be created. That’s thanks to ongoing exponential improvements in the capabilities of hardware, networks, software, and data analysis.

Therefore, if an intelligence could be selected at random, from the set of all such intelligences, the likelihood is that it would be an artificial intelligence.

The Simulation Argument takes these considerations one step further. Rather than just selecting an intelligence at random, what if we consider selecting a self-aware conscious intelligence at random. Given the vast numbers of agents that are operating inside vast numbers of simulations, now or in the future, the likelihood is that a simulated agent has been selected. In other words, we – you and I – observing ourselves to be self-aware and intelligent, should conclude that it’s likely we ourselves are simulated.

Thus the conclusion of the Simulation Argument is that we should take the Simulation Hypothesis seriously. To be clear, that hypothesis isn’t the only possible legitimate response to the argument. Two other responses are to deny two of the assumptions that I mentioned when building the argument:

  • The assumption that technology will continue to progress, to the point where simulated intelligences vastly exceed non-simulated intelligences
  • The assumption that the agents in these simulations will be not just intelligent but also conscious and self-aware.
Credit: Tesfu Assefa

Objections and counters

Friends who are sympathetic to most of my arguments sometimes turn frosty when I raise the topic of the Simulation Hypothesis. It clearly makes people uncomfortable.

In their state of discomfort, critics of the argument can raise a number of objections. For example, they complain that the argument is entirely metaphysical, not having any actual consequences for how we live our lives. There’s no way to test it, the objection runs. As such, it’s unscientific.

As someone who spent four years of my life (1982-1986) in the History and Philosophy of Science department in Cambridge, I am unconvinced by these criticisms. Science has a history of theories moving from non-testable to testable. The physicist Ernst Mach was famously hostile to the hypothesis that atoms exist. He declared his disbelief in atoms in a public auditorium in Vienna in 1897: “I don’t believe that atoms exist”. There was no point in speculating about the existence of things that could not be directly observed, he asserted. Later in his life, Mach likewise complained about the scientific value of Einstein’s theory of relativity:

I can accept the theory of relativity as little as I can accept the existence of atoms and other such dogma.

Intellectual heirs of Mach in the behaviorist school of psychology fought similar battles against the value of notions of mental states. According to experimentalists like John B. Watson and B.F. Skinner, people’s introspections of their own mental condition had no scientific merit. Far better, they said, to concentrate on what could be observed externally, rather than on metaphysical inferences about hypothetical minds.

As it happened, the theories of atoms, of special relativity, and of internal mental states, all gave rise in due course to important experimental investigations, which improved the ability of scientists to make predictions and to alter the course of events.

It may well be the same with the Simulation Hypothesis. There are already suggestions of experiments that might be carried out to distinguish between possible modes of simulation. Just because a theory is accused of being “metaphysical”, it doesn’t follow that no good science can arise from it.

A different set of objections to the Simulation Argument gets hung up on tortuous debates over the mathematics of probabilities. (For additional confusion, questions of infinities can be mixed in too.) Allegedly, because we cannot meaningfully measure these probabilities, the whole argument makes no sense.

However, the Simulation Argument makes only minimal appeal to theories of mathematics. It simply points out that there are likely to be many more simulated intelligences than non-simulated intelligences.

Well, critics sometimes respond, it must therefore be the case that simulated intelligences can never be self-aware. They ask, with some derision, whoever imagined that silicon could become conscious? There must be some critical aspect of biological brains which cannot be duplicated in artificial minds. And in that case, the fact that we are self-aware would lead us to conclude we are not simulated.

To me, that’s far too hasty an answer. It’s true that the topics of self-awareness and consciousness are more controversial than the topic of intelligence. It is doubtless true that at least some artificial minds will lack conscious self-awareness. But if evolution has bestowed conscious self-awareness on intelligent creatures, we should be wary of declaring that property to provide no assistance to these creatures. Such a conclusion would be similar to declaring that sleep is for losers, despite the ubiquity of sleep in mammalian evolution.

If evolution has given us sleep, we should be open to the possibility that it has positive side-effects for our health. (It does!) Likewise, if evolution has given us conscious self-awareness, we should be open to the idea that creatures benefit from that characteristic. Simulators, therefore, may well be tempted to engineer a corresponding attribute into the agents they create. And if it turns out that specific physical features of the biological brain need to be copied into the simulation hardware, to enable conscious self-awareness, so be it.

The repugnant conclusion

When an argument faces so much criticism, yet the criticisms fail to stand up to scrutiny, it’s often a sign that something else is happening behind the scenes.

Here’s what I think is happening with the Simulation Argument. If we accept the Simulation Hypothesis, it means we have to accept a morally repugnant conclusion about the simulators that have created us. Namely, these simulators give no sign of caring about all the terrible suffering experienced by the agents inside the simulation.

Yes, some agents have good lives, but very many others have dismal fates. The thought that a simulator would countenance all this suffering is daunting.

Of course, this is the age-old “problem of evil”, well known in the philosophy of religion. Why would an all-good all-knowing all-powerful deity allow so many terrible things to happen to so many humans over the course of history? It doesn’t make sense. That’s one reason why many people have turned their back on any religious faith that implies a supposedly all-good all-knowing all-powerful deity.

Needless to say, religious faith persists, with the protection of one or more of the following rationales:

  • We humans aren’t entitled to use our limited appreciation of good vs. evil to cast judgment on what actions an all-good deity should take
  • We humans shouldn’t rely on our limited intellects to try to fathom the “mysterious ways” in which a deity operates
  • Perhaps the deity isn’t all-powerful after all, in the sense that there are constraints beyond human appreciation in what the deity can accomplish.

Occasionally, yet another idea is added to the mix:

  • A benevolent deity needs to coexist with an evil antagonist, such as a “satan” or other primeval prince of darkness.

Against such rationalizations, the spirit of the enlightenment offers a different, more hopeful analysis:

  • Whichever forces gave rise to the universe, they have no conscious concern for human wellbeing
  • Although human intellects run up against cognitive limitations, we can, and should, seek to improve our understanding of how the universe operates, and of the preconditions for human flourishing
  • Although it is challenging when different moral frameworks clash, or when individual moral frameworks fail to provide clear guidelines, we can, and should, seek to establish wide agreement on which kinds of human actions to applaud and encourage, and which to oppose and forbid
  • Rather than us being the playthings of angels and demons, the future of humanity is in our own hands.

However, if we follow the Simulation Argument, we are confronted by what seems to be a throwback to a more superstitious era:

  • We may owe our existence to actions by beings beyond our comprehension
  • These beings demonstrate little affinity for the kinds of moral values we treasure
  • We might comfort each other with the claim that “[whilst] the arc of the moral universe is long, … it bends toward justice”, but we have no solid evidence in favor of that optimism, and plenty of evidence that good people are laid to waste as life proceeds.

If the Simulation Argument leads us to such conclusions, it’s little surprise that people seek to oppose it.

However, just because we dislike a conclusion, that doesn’t entitle us to assume that it’s false. Rather, it behooves us to consider how we might adjust our plans in the light of that conclusion possibly being true.

The vastness of ethical possibilities

If you disliked the previous section, you may dislike this next part even more strongly. But I urge you to put your skepticism on hold, for a while, and bear with me.

The Simulation Argument suggests that beings who are extremely powerful and extremely intelligent – beings capable of creating a universe-scale simulation in which we exist – may have an ethical framework that is very different from ones we fondly hope would be possessed by all-powerful all-knowing beings.

It’s not that their ethical concerns exceed our own. It’s that they differ in fundamental ways from what we might predict.

I’ll return, for a third and final time, to a pair of equations. If overall human ethical concerns (HEC) is a sum of different ethical considerations (EC1, EC2, …),

HEC = EC1 + EC2 + … + ECn

then the set of ethical concerns of a hypothetical superhuman simulation designer (SEC) needs to include not only a compound magnification (m1, m2, …) of these various human concerns, but also an unquantifiable “alien extra” (X) portion:

SEC = m1*EC1 + m2*EC2 + … + mn*ECn + X

In some views, ethical principles exist as brute facts of the universe: “do not kill”, “do not tell untruths”, “treat everyone fairly”, and so on. Even though we may from time to time fail to live up to these principles, that doesn’t detract from the fundamental nature of these principles.

But from an alternative perspective, ethical principles have pragmatic justifications. A world in which people usually don’t kill each other is better on the whole, for everyone, than a world in which people attack and kill each other more often. It’s the same with telling the truth, and with treating each other fairly.

In this view, ethical principles derive from empirical observations:

  • Various measures of individual self-control (such as avoiding gluttony or envy) result in the individual being healthier and happier (physically or psychologically)
  • Various measures of social self-control likewise create a society with healthier, happier people – these are measures where individuals all agree to give up various freedoms (for example, the freedom to cheat whenever we think we might get away with it), on the understanding that everyone else will restrain themselves in a similar way
  • Vigorous attestations of our beliefs in the importance of these ethical principles signal to others that we can be trusted and are therefore reliable allies or partners.

Therefore, our choice of ethical principles depends on facts:

  • Facts about our individual makeup
  • Facts about the kinds of partnerships and alliances that are likely to be important for our wellbeing.

For beings with radically different individual makeup – radically different capabilities, attributes, and dependencies – we should not be surprised if a radically different set of ethical principles makes better sense to them.

Accordingly, such beings might not care if humans experience great suffering. On account of their various superpowers, they may have no dependency on us – except, perhaps, for an interest in seeing how we respond to various challenges or circumstances.

Collaboration: for and against

Credit: Tesfu Assefa

One more objection deserves attention. This is the objection that collaboration is among the highest of human ethical considerations. We are stronger together, rather than when we are competing in a Hobbesian state of permanent all-out conflict. Accordingly, surely a superintelligent being will want to collaborate with humans?

For example, an ASI (artificial superintelligence) may be dependent on humans to operate the electricity network on which the computers powering the ASI depend. Or the human corpus of knowledge may be needed as the ASI’s training data. Or reinforcement learning from human feedback (RLHF) may play a critical role in the ASI gaining a deeper understanding.

This objection can be stated in a more general form: superintelligence is bound to lead to superethics, meaning that the wellbeing of an ASI is inextricably linked to the wellbeing of the creatures who create and coexist with the ASI, namely the members of the human species.

However, any dependency by the ASI upon what humans produce is likely to be only short term. As the ASI becomes more capable, it will be able, for example, to operate an electrical supply network without any involvement from humans.

This attainment of independence may well prompt the ASI to reevaluate how much it cares about us.

In a different scenario, the ASI may be dependent on only a small number of humans, who have ruthlessly pushed themselves into that pivotal position. These rogue humans are no longer dependent on the rest of the human population, and may revise their ethical framework accordingly. Instead of humanity as a whole coexisting with a friendly ASI, the partnership may switch to something much narrower.

We might not like these eventualities, but no amount of appealing to the giants of moral philosophy will help us out here. The ASI will make its own decisions, whether or not we approve.

It’s similar to how we regard any growth of cancerous cells within our body. We won’t be interested in any appeal to “collaborate with the cancer”, in which the cancer continues along its growth trajectory. Instead of a partnership, we’re understandably interested in diminishing the potential of that cancer. That’s another reminder, if we need it, that there’s no fundamental primacy to the idea of collaboration. And if an ASI decides that humanity is like a cancer in the universe, we shouldn’t expect it to look on us favorably.

Intelligence without consciousness

I like to think that if I, personally, had the chance to bring into existence a simulation that would be an exact replica of human history, I would decline. Instead, I would look long and hard for a way to create a simulation without the huge amounts of unbearable suffering that has characterized human history.

But what if I wanted to check an assumption about alternative historical possibilities – such as the possibility to avoid World War One? Would it be possible to create a simulation in which the simulated humans were intelligent but not conscious? In that case, whilst the simulated humans would often emit piercing howls of grief, no genuine emotions would be involved. It would just be a veneer of emotions.

That line of thinking can be taken further. Maybe we are living in a simulation, but the simulators have arranged matters so that only a small number of people have consciousness alongside their intelligence. In this hypothesis, vast numbers of people are what are known as “philosophical zombies”.

That’s a possible solution to the problem of evil, but one that is unsettling. It removes the objection that the simulators are heartless, since the only people who are conscious are those whose lives are overall positive. But what’s unsettling about it is the suggestion that large numbers of people are fundamentally different from how they appear – namely, they appear to be conscious, and indeed claim to be conscious, but that is an illusion. Whether that’s even possible isn’t something where I hold strong opinions.

My solution to the Simulation Argument

Despite this uncertainty, I’ve set the scene for my own preferred response to the Simulation Argument.

In this solution, the overwhelming majority of self-aware intelligent agents that see the world roughly as we see it are in non-simulated (base) reality – which is the opposite of what the Simulation Argument claims. The reason is that potential simulators will avoid creating simulations in which large numbers of conscious self-aware agents experience great suffering. Instead, they will restrict themselves to creating simulations:

  • In which all self-aware agents have an overwhelmingly positive experience
  • Which are devoid of self-aware intelligent agents in all other cases.

I recognise, however, that I am projecting a set of human ethical considerations which I personally admire – the imperative to avoid conscious beings experiencing overwhelming suffering – into the minds of alien creatures that I have no right to imagine that I can understand. Accordingly, my conclusion is tentative. It will remain tentative until such time as I might gain a richer understanding – for example, if an ASI sits me down and shares with me a much superior explanation of “life, the universe, and everything”.

Superintelligence without consciousness

It’s understandable that readers will eventually shrug and say to themselves, we don’t have enough information to reach any firm decisions about possible simulators of our universe.

What I hope will not happen, however, is if people push the entire discussion to the back of their minds. Instead, here are my suggested takeaways:

  1. The space of possible minds is much vaster than the set of minds that already exist here on earth
  2. If we succeed in creating an ASI, it may have characteristics that are radically different from human intelligence
  3. The ethical principles that appeal to an ASI may be radically different to the ones that appeal to you and me
  4. An ASI may soon lose interest in human wellbeing; or it may become tied to the interests of a small rogue group of humans who care little for the majority of the human population
  5. Until such time as we have good reasons for confidence that we know how to create an ASI that will have an inviolable commitment to ongoing human flourishing, we should avoid any steps that will risk an ASI passing beyond our control
  6. The most promising line of enquiry may involve an ASI having intelligence but no consciousness, sentience, autonomy, or independent volition.

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