Deep fakes: What’s next? Anticipating new twists and turns in humanity’s oldest struggle

Posted on by David Wood

Fake news that the Pope endorsed Donald Trump (a story that was shared more widely than any legitimate news story that year). A fake picture of former US VP Michael Pence in his youth seemingly as a gay porn star. Fake audio of UK political leader Keir Starmer apparently viciously berating a young volunteer assistant. Another fake audio of London mayor Sadiq Khan apparently giving priority to a pro-Palestinian march over the annual Remembrance Day walk-past by military veterans. Fake videos of apparent war atrocities. Fake pornographic videos of megastar pop celebrities.

What’s next? And how much does it really matter?

Some observers declare that there’s nothing new under the sun, and that there’s no special need to anticipate worse to come. Society, they say, already knows how to deal with fake news. Fake news may be unpleasant – and it’s sometimes hilarious – but we just have to keep calm and carry on.

I strongly disagree, as I’ll explain below. I’ll review ten reasons why fake news is likely to become worse in the months ahead. Then I’ll suggest ten steps that can be taken to regain our collective sanity.

It remains to be determined whether these ten steps will be sufficient, or whether we’ll all sink into a post-truth swamp, in which sneering suspicion displaces diligent understanding, fake science displaces trustworthy science, fake journalism displaces trustworthy journalism, and fake politicians seize power and impose their dictatorial whims.

Credit: David Wood via Midjourney

Deception: the back story

It’s not flattering to say it, but we humans have been liars since before the dawn of history. And, just as important, we have been self-deceivers as well: we deceive ourselves in order to be more successful in deceiving others.

In case that idea offends you, I invite you to delve into the evidence and analysis offered in, for example:

Credit: Book publishers’ websites (links above)

We implore our children to be truthful but also guide them to know when to tell white lies – “thank you for this lovely present, it’s just what I wanted!” And the same ancient books of the Bible that command us “do not bear false witness” appear to celebrate deceit when practiced by figures such as Jacob, Rachel, Rebekah, and Tamar.

I could tell you, as well, that the ancient Greek dramatist Aeschylus, known as ‘the father of tragedy’, made this pithy observation two and half millennia ago: “Truth is the first casualty in war”. One tragedy – war – births another – deception.

As it happens, it seems likely that this quotation is a misattribution. I’ll come back to that point later, when talking, not about deception, but about solutions to deception. But regardless of whoever first uttered that saying, we can appreciate the insight it contains. In times of bitter conflict, there are special incentives to mislead observers – about the casualties we have suffered, about the casualties we have inflicted on opposing forces, about our military plans for the future, and much more.

It’s not just war that provides an incentive to deceive. It’s the same with politics: opposing parties compete to set the narrative, and individual politicians seek to climb past each other on what Benjamin Disraeli dubbed “the greasy pole” of political intrigue. It’s the same with commerce, with companies ready to spread misleading ‘FUD’ (fear, uncertainty, and doubt) regarding the comparative strengths of various forthcoming products and services. And it’s the same in private life, as we seek to portray ourselves in a favorable light in the eyes of family and friends, hiding our physical and psychological warts.

In this sense, deception is old news. We’ve had ‘fake news’ for as long as there has been ‘news’.

It’s tempting, therefore, to yawn when people draw attention to more recent examples of fake news and deception.

But that would be a giant mistake.

It’s technology that’s making the difference. Technology ramps up the possibilities for fake news to be even more deceptive, more credible, more ubiquitous, more personal, and more effective. Led by leaps in capabilities of AI systems, technology is enabling dramatic new twists in the struggle between truth and lies. It’s becoming even harder to distinguish between trustworthy and untrustworthy information.

The joy of misinformation. What harm could it cause? (Credit: David Wood via Midjourney)

If we fail to anticipate these developments, we’re likely to succumb to new waves of deception. The consequences may be catastrophic.

But forewarned is forearmed. By drawing on insights from humanity’s better experiences, we should be able to create technologies, processes, and institutions that help us to block these oncoming waves.

Ten twists

1. Fake news at scale

If at first you fail, why not try again?

You tried to deceive your target audience, but they were not swayed. This time, they saw through your lies. Or perhaps they didn’t even pay attention.

But if trying is cheap and quick, you can try again, this time with a different false narrative, expressed in a different voice.

What’s changed is that it’s much cheaper to try again. You can take advantage of automation, always-on networks, social media, and generative AI, to create and distribute new pieces of fake news. It’s mass-production for lies.

You’re not constrained by only creating one bot on social media. You can create armies of them.

You’re not constrained by having to write text yourself, or create suitably misleading images. You can obtain good results from a few clicks of a mouse.

The result is that discussion is being flooded with deliberately false narratives.

2. Fake news that earns money

Some false narratives are designed to try to change people’s minds. They want to change voting decisions, purchasing decisions, relationship decisions, and so on.

But other false narratives have a different purpose: to earn money via advertising clicks or affiliate marketing revenue share.

Viewers are attracted to websites by content that is outrageous, inflammatory, intriguing, or funny. They spend more time on these sites to explore the other content there, enjoying being outraged, inflamed, intrigued, or simply humored. And while on these sites, they may click on other links that generate revenue for the owners of the site.

In this case, the content creators have no special interest in whether the content matches their own political or philosophical outlooks. They produce whatever earns them the most clicks. Indeed, some clickbait merchants set up websites posting contradictory stories, to catch traffic from both sides of the political spectrum.

As a sad side-effect, people’s minds become increasingly confused. Being misled by fake content, they become less able to distinguish fantasy from reality.

3. Fake news with a personal appeal

It’s not just that fake news is being created on a greater scale than ever before. It’s being created with a greater variety than ever before.

Technology makes it easier to create different variants of the same false narrative. Some variants can be sent to people who are supporters of Candidate A within Party P. A different variant can be sent to people who support Candidate B within Party P. Yet other different variants target people whose favored candidates are from Party Q, Party R, and so on.

More than that: once software has learned which kind of pretty face each person is likely to look at – or which kinds of music make each person want to listen – these variants can easily be generated too, and directed to each target.

4. Fake news based on footprints

You might wonder: how does software know that I am likely to be distracted by particular kinds of pretty faces, or particular kinds of music?

That’s where extensive data gathering and analysis come to the fore. We are each constantly generating online footprints.

For example, Facebook notices that when it places a chess puzzle in my timeline, I tend to click on that conversation, to consider the position in more detail. Facebook observes my interest in these puzzles. Soon, more chess puzzles are being shown to me.

That particular inference is relatively straightforward. Other inferences depend on a wider review of my online activity – which posts I ‘like’, which posts I ‘hide’, and so on.

Astute robots can learn more from our footprints than we expected (Credit: David Wood via Midjourney)

The algorithms make all kinds of deductions from such reviews. They’re not always correct, not even close. But the AI systems that create personalized fake news have greater numbers of positive hits than those that don’t.

5. Fake news that builds on top of truth

The best lies mix truth with untruth. These lies are especially effective if the truth in question is one that much of society likes to suppress.

Consider a simple example. A leaked document here, a whistleblower there – a few hints suggest something fishy is going on: there is bureaucratic corruption and nepotism within a political state. Then the news-faker adds the unjustified conclusion: the government in question is irretrievably corrupt. Hence the conclusion: kick all these politicians out of power!

Again: a narrative might give a number of examples of people experiencing remission from long-standing diseases, despite forecasts from white-coated doctors that the disease was fatal. Then it adds the lie: what matters most in healthcare is your personal attitude, rather than expensive drugs that Big Pharma are trying to sell. Therefore: stop listening to your doctor, and instead purchase my course in positive thinking for $29.99 a month!

Again: members of some minorities suffered appalling abuses in trials of various medical procedures, where there was no informed consent, and where there was an apparent casual disregard for the suffering entailed. And then the lie: present-day society is incorrigibly racist and irredeemably exploitative. Therefore: it’s time to wield pitchforks!

The cleverest fake news combines this principle with the previous one. It works out our belief-systems from our online footprints – it figures out what we already suspect to be true, or hope to be true, even though the rest of society tends to think differently. Then it whips up a fake narrative from beliefs we support plus the new message it’s trying to inject into our minds.

In this way, it flatters us, in order to better mislead us.

No wonder that we often fall for that kind of deception.

6. Fake news that weaponizes friendships

Each of us is more likely to pay attention to a message if it comes from a person that we think we like – someone we perceive as one of our special friends.

If our friend is concerned about a topic, it makes us more likely to be concerned about it too – even if, previously, we might not have given that topic a second thought.

This is where the sinister power of the systems that manufacture fake news reaches higher levels. These systems invest time to create fake personas – people who we welcome as our ‘friends’ on social media.

At first, these friends say nothing out of the ordinary. We forget whether or not we met them in real life. Their names become increasingly familiar to us. We imagine we know lots about them – even though their entire backstory is fictitious.

And that’s when the poisonous messages start seeping into your conversations and then into your thoughts. And without you realizing what has happened, a fake friend has led you into a fake idea.

7. Fake news with amplification support

If we hear the same opinion from multiple sources, we may at first resist the idea, but then start to accept it.

That’s especially true if the opinion receives apparent support from apparent credentialed experts.

Thus when some fake audio is posted to social media, other fake posts soon accompany it. “I’m an expert in audio authentication”, a bot declares. “I’ve studied the clip carefully, and I assure you it’s genuine”.

If we don’t look closely, we’ll fail to spot that the credentials are bogus, and that there’s no real-world audio expert behind these claims.

The greater the number (and the greater the variety) of the apparent endorsements, the easier it becomes for some of these fake endorsements to bypass our critical faculties and to change our minds.

8. Fake news that exploits our pride

We all like to tell ourselves: we’re not the kind of person who falls for a simple conjuring trick.

Other people – those not so smart as us, we think – might be misled by dubious claims in advertisements or social media memes. Not us!

This has been called the bias blind spot – the cognitive bias that says “other people have cognitive biases, but not me!”

But recall that our ability to deceive ourselves is key to our ability to deceive others. If we are conscious of our lies, astute listeners will notice it. That’s why our subconscious needs to mislead our conscious mind before we in turn can mislead other people.

In the same way, it is an inflated self-confidence that we are good reasoners and good observers that can set us up for the biggest failures.

Couple a misplaced pride in our own critical faculties with the warm feelings that we have developed for friends (either fake online personas, as covered above, or real-world friends who have already fallen into social media rabbit holes), and we are set up to be suckered.

9. Fake news that exploits alienation

Pride isn’t the only emotion that can tempt us into the pit of fake news. Sometimes it can be a sense of grievance or of alienation that we cling to.

Unfortunately, although some aspects of the modern world feature greater human flourishing than ever before, other aspects increase the chances of people nurturing grievances:

  • The inability of large segments of the population to afford good healthcare, good education, or good accommodation
  • The constant barrage of bad news stories from media, 24 hours a day
  • A matching barrage of stories that seem to show the “elites” of society as being out-of-touch, decadent, uncaring, and frivolous, wallowing in undeserved luxury.

As a result, fake news narratives can more easily reach fertile soil – unhappy minds skip any careful assessment of the validity of the claims made.

When you’re fed up with the world, it’s easier to lead you astray (Credit: David Wood via Midjourney)

10. Fake news with a lower barrier to entry

Perhaps you’re still thinking: none of the above is truly novel.

In a way, you would be correct. In past times, clever operators with sufficient resources could devise falsehoods that misled lots of people. Traditional media – including radio and newspapers – were spreading destructive propaganda long before the birth of the Internet.

But the biggest difference, nowadays, is how easy it is for people to access the tools that can help them achieve all the effects listed above.

The barrier to entry for purveyors of far-reaching fake news is lower than ever before. This is an age of ‘malware as a service’, dark net tutorials on guerrilla information warfare, and turnkey tools and databases.

It’s an age where powerful AI systems can increasingly be deployed in service of all the above methods.

Happily, as I’ll discuss shortly, these same AI systems can provide part of the solution to the problem of ubiquitous fake news. But only part of the solution.

Interlude: a world without trust

First, a quick reminder of the bad consequences of fake news.

It’s not just that people are deceived into thinking that dangerous politicians are actually good people, and, contrariwise, that decent men and women are actually deplorable – so that electors are fooled into voting the dangerous ones into power.

It’s not just that people are deceived into hating an entire section of society, seeing everyone in that grouping as somehow subhuman.

It’s not just that people are deceived into investing their life savings into bogus schemes in which they lose everything.

It’s not just that people are deceived into rejecting the sound advice of meticulous medical researchers, and instead adopt unsafe hyped-up treatments that have fearful health consequences.

All of these examples of unsound adoption of dangerous false beliefs are, indeed, serious.

But there’s another problem. When people see that much of the public discourse is filled with untrustworthy fake news, they are prone to jump to the conclusion that all news is equally untrustworthy.

As noted by Judith Donath, fellow at Harvard University’s Berkman Klein Center for Internet & Society and founder of the Sociable Media Group at the MIT Media Lab,

A pernicious harm of fake news is the doubt it sows about the reliability of all news.

Thus the frequent lies and distortions of fringe news sites like InfoWars, Natural News, and Breitbart News lead many people to conclude that all media frequently publish lies. Therefore nothing should be trusted. And the phrase “mainstream media” becomes a sneer.

(They find some justification for this conclusion in the observation that all media make some mistakes from time to time. The problem, of course, is in extrapolating from individual instances of mistakes to applying hostile doubt to all news.)

Baroness Onora O’Neill of the Faculty of Philosophy at the University of Cambridge commenced her series of Reith Lectures in 2002 by quoting Confucius:

Confucius told his disciple Tsze-kung that three things are needed for government: weapons, food, and trust. If a ruler can’t hold on to all three, he should give up the weapons first and the food next. Trust should be guarded to the end: ‘without trust we cannot stand’.

Sadly, if there is no trust, we’re likely to end up being governed by the sort of regimes that are the furthest from deserving trust.

It’s as the German historian and philosopher Hannah Arendt warned us in her 1951 book The Origins of Totalitarianism:

The ideal subject of totalitarian rule is not the convinced Nazi or the convinced Communist, but people for whom the distinction between fact and fiction, in other words, the reality of experience, and the distinction between true and false… people for whom those distinctions no longer exist.

However, the technologies of the 2020s put fearsome possibilities into our grasp that writers in 1951 (like Arendt) and in 2002 (like O’Neill) could hardly have imagined.

Big Brother will be watching, from every angle (Credit: David Wood via Midjourney)

In previous generations, people could keep their inner thoughts to themselves, whilst outwardly kowtowing to the totalitarian regimes in which they found themselves. But with ten-fold twisted fake news, even our inner minds will be hounded and subverted. Any internal refuge of independent thinking is likely to be squelched. Unless, that is, we are wise enough to take action now to prevent that downward spiral.

Regaining trust

What can be done to re-establish trust in society?

Having anticipated, above, ten ways in which the problem of fake news is becoming worse, I now offer an equal number of possible steps forward.

1. Education, education, education

Part of growing up is to learn not to trust so-called 419 scam emails. (The number 419 refers to the section of the Nigerian Criminal Code that deals with fraud.) If someone emails us to say they are a prince of a remote country and they wish to pass their inheritance to us – provided we forward them some hard cash first – this is almost certainly too good to be true.

We also learn that seeing is not believing: our eyes can deceive us, due to optical illusions. If we see water ahead of us on a desert road, that doesn’t mean the water is there.

Similarly, we all need to learn the ways in which fake news stories can mislead us – and about the risks involved in thoughtlessly spreading such news further.

These mechanisms and risks should be covered in educational materials for people of all ages.

It’s like becoming vaccinated and developing resistance to biological pathogens. If we see at first hand the problems caused by over-credulous acceptance of false narratives, it can make us more careful on the next occasion. 

But this educational initiative needs to do more than alert people to the ways in which fake news operates. It also needs to counter the insidious view that all news is equally untrustworthy – the insidious view that there’s no such thing as an expert opinion.

This means more than teaching people the facts of science. It means teaching people the methods used by science to test hypotheses, the reasons why science assesses various specific hypotheses as being plausible. Finally, it means teaching people, “here are the reasons to assign a higher level of trust to specific media organizations”.

That takes us to the second potential step forward.

2. Upholding trustworthy sources

Earlier, I mentioned that a quote often attributed to the fifth century BC writer Aeschylus was almost certainly not actually said by him.

What gives me confidence in that conclusion?

It’s because of the reliance I place in one online organization, namely Quote Investigator. In turn, that reliance arises from:

  • The careful way in which pages on that site reference the sources they use
  • The regular updates the site makes to its pages, as readers find additional relevant information
  • The fact that, for all the years I’ve been using that site, I can’t remember ever being misled by it
  • The lack of any profit motivation for the site
  • Its focus on a particular area of research, rather than spreading its attention to wider topics
  • Positive commendations for the site from other researchers that have gained and maintained a good reputation.

Other organizations have similar aspirations. Rather than “quote checking”, some of them specialize in “fact checking”. Examples include:

Credit: Fact-checking websites (links above)

These sites have their critics, who make various allegations of partisan bias, overreliance on supposed experts with questionable credentials, subjective evaluations, and unclear sources of funding.

My own judgment is that these criticisms are mainly misplaced, but that constant vigilance is needed.

I’ll go further: these sites are among the most important projects taking place on the planet. To the extent that they fall short, we should all be trying to help out, rather than denigrating them.

3. Real-time fact-checking

Fact checking websites are often impressively quick in updating their pages to address new narratives. However, this still leaves a number of problems:

  • People may be swayed by a false narrative before that narrative is added to a fact-checking site
  • Even though a piece of fake news is soundly debunked on a fact-checking site, someone may not be aware of that debunking
  • Even if someone subsequently reads an article on a fact-checking site that points out the flaws of a particular false narrative, that narrative may already have caused a rewiring of the person’s belief systems at a subconscious level – and that rewiring may persist even though the person learns about the flaws in the story that triggered these subconscious changes
  • The personalization problem: false narratives tailored to individual targets won’t be picked up by centralized fact-checking sites.

AI could hold part of the answer. Imagine if our digital media systems included real-time fact-checking analyses. That’s part of the potential of AI systems. These real-time notifications would catch the false information before it has a chance to penetrate deeply into our brain.

Our email applications already do a version of this: flagging suspicious content. The application warns us: this email claims to come from your bank, but it probably doesn’t, so take care with it. Or: the attachment to this email purports to be a PDF, but it’s actually an executable file that will likely cause damage.

Likewise, automated real-time fact-checking could display messages on the screen, on top of the content that is being communicated to us, saying things like:

  • “The claim has been refuted”
  • “Note that the graph presented is misleading”
  • “This video has been doctored from its original version”
  • “This audio has no reliable evidence as to its authenticity”
  • “There is no indication of a cause-and-effect relationship between the facts mentioned”

In each case, ideally the warning message will contain a link to where more information can be found.

4. Decentralized fact-checking

The next question that arises is: how can people be confident in relying on specific real-time fact-checkers?

We can already imagine their complaints:

  • “This fact-checker is wokism gone mad”
  • “This fact-checker serves Google, not me”
  • “This fact-checker serves the government, not me”
  • “I prefer to turn off the fact-checker, to receive my news free from censorship”

There’s no one easy answer to these objections. Each step I describe in this list of ten is designed to reduce some of the apprehension.

But an important step forward would be to separate the provision of content from the fact-checking layer. The fact-checking layer, rather than being owned and operated by the commercial entity that delivers the media, would ideally transcend individual corporations. For example, it could operate akin to Wikipedia, although it would likely need more funding than Wikipedia currently receives.

Further developing this model, the fact-checking software could have various settings that users adjust, reflecting their own judgment about which independent sources should be used for cross-checking.

Maybe the task is too dangerous to leave to just one organization: then another model would involve the existence of more than one option in the fact-checking field, with users being able to select one – or a bunch – to run on their devices.

5. Penalties for dangerous fakes

As well as trying to improve the identification of fake news, it’s important to change the incentives under which fake news is created and distributed. There are roles for ‘sticks’ (penalties) as well as ‘carrots’ (rewards).

Regarding penalties, society already imposes penalties:

  • When advertisements make misleading or unfounded claims
  • When companies make misleading or unfounded claims in their financial statements
  • When people make libelous claims about each other.

Fines or other punishments could be used in cases where people knowingly distribute misleading narratives, when the consequences involve clear harm (for example, a riot).

This proposal makes some people nervous, as they see it as an intrusion on freedom of expression, or a block on satire. They fear that governments would use these punishments to clamp down on statements that are embarrassing to them.

That’s why monitoring and prosecuting such cases needs to be done independently – by a police force and judiciary that operates at arms’ length from the government of the day.

This principle of separation of powers already applies to many other legal regulations, and could surely work for policing fake news.

Related, there’s a case for wider collection and publication of statistics of reliability. Just as hospitals, schools, and many other parts of society have statistics published about their performance, media organizations should receive the same scorecard.

In this way, it would be easy to know which media channels have a casual relationship with the truth, and which behave more cautiously. In this way, investment funds or other sources of financing could deny support to organizations whose trustworthiness ratings drop too low. This kind of market punishment would operate alongside the legal punishment that applies to more egregious cases.

6. A coalition for integrity

Some of the creators of fake news won’t be deterred by threats of legal punishment. They already operate beyond the reaches of the law, in overseas jurisdictions, or anonymously and secretly.

Nevertheless, there are still points of crossover, where new content is added into media channels. It is at these points where sanctions can be applied. Media organizations that are lax in monitoring the material they receive would then become liable for damage arising.

This will be hard to apply for communications systems such as Telegram, WhatsApp, and Signal, where content is encrypted from one end of a communication to the other. In such cases, the communications company doesn’t know what is being transmitted.

Indeed, it is via such closed communications systems that fake news often spreads these days, with Telegram a particularly bad offender.

There’s a case to be made for a coalition of every organization that values truthfulness and trustworthiness over the local benefits of spreading false information.

Forming a Coalition for Integrity (Credit: David Wood via Midjourney)

People who support this ‘coalition for integrity’ would share information about:

  • Entry points used by fake news providers to try to evade detection
  • Identification of fake news providers
  • Ways in which providers of fake news are changing their methods – and how these new methods can be combated.

Regardless of differences in political or philosophical outlook among members of this coalition, they have a common interest in defending truthfulness versus deception. They should not allow their differences to hinder effective collaboration in support of that common purpose.

7. Making trust everyone’s business

In recent decades, a variety of new job titles have been created at the highest levels within companies and organizations, such as:

  • Chief Design Officer
  • Chief Innovation Officer
  • Chief Quality Officer
  • Chief Security Officer

None of these posts free other members of the company from their responsibility for design, innovation, quality or security. These values are universal to everyone in the organization as they go about their duties. Nevertheless, the new ‘chief’ provides a high-level focus on the topic.

It should be the same with a new set of ‘Chief Trust Officers’. These executives would find ways to keep reminding personnel about:

  • The perils arising if the organization gains a reputation for being untrustworthy
  • Methods and procedures to follow to build and maintain a trustworthy reputation for the organization
  • Types of error that could result in dangerous false narratives being unwittingly transmitted

My assessment is that the organizations who appoint and support Chief Trust Officers (or equivalent) are the ones most likely to succeed in the turbulent times ahead.

8. Encouraging openness

To be clear, education often fails: people resist believing that they can be taken in by false information.

We like to think of ourselves as rational people, but a more accurate description is that we are a rationalizing species. We delight in finding ways to convince ourselves that it is fine to believe the things that we want to believe (even in the face of apparent evidence against these beliefs).

That’s why bombarding people with education often backfires. Rather than listening to these points, people can erect a strong shield of skepticism, as they prepare to lash out at would-be educators.

Indeed, we all know people who are remarkably clever, but they deploy their cleverness in support of profoundly unwise endeavors.

This state of affairs cannot be solved merely by pumping in more facts and arguments. Instead, different approaches are required, to encourage a greater openness of spirit.

One approach relies on the principle mentioned earlier, in which people pay more attention to suggestions from their close friends. Therefore, the best way to warn people they are about to fall for dangerous information is for them to be warned by people they already trust and respect.

Another approach is to find ways to put people in a better mood all round. When they have a compassionate, optimistic mindset, they’re more likely to listen carefully to warnings being raised – and less likely to swat away these warnings as an unwelcome annoyance.

It’s not enough to try to raise rational intelligence – rather, we must raise compassionate intelligence: an intelligence that seeks wisdom and value in interactions even with people previously regarded as a threat or enemy.

This is a different kind of education. Not an education in rationality, but rather an education in openness and compassion. It may involve music, meditation, spending time in nature, biofeedback, and selected mind-transforming substances. Of course, these have potential drawbacks as well as potential benefits, but since the upsides are so high, options need to be urgently explored.

9. A shared positive vision

Another factor that can predispose people to openness and collaboration, over closed-mindedness and stubborn tribal loyalties, is a credible path forward to a world with profound shared benefits.

When people anticipate an ongoing struggle, with zero-sum outcomes and continual scarcity of vital resources, it makes them mentally hostile and rigid.

Indeed, if they foresee such an ongoing conflict, they’ll be inclined to highlight any available information – true or fake – that shows their presumed enemies in a bad light. What matters to them in that moment is anything that might annoy, demoralize, or inflame these presumed enemies. They seize on fake news that does this, and also brings together their side: the set of people who share their sense of alienation and frustration with their enemies.

That is why the education campaign that I anticipate needs a roadmap to what I call a sustainable superabundance, in which everyone benefits. If this vision permeates both hearts and minds, it can inspire people to set and respect a higher standard of trustworthiness. Peddlers of fake news will discover, at that point, that people have lost interest in their untruths.

10. Collaborative intelligence

I do not claim that the nine steps above are likely to be sufficient to head off the coming wave of dangerous fake news.

Instead, I see them as a starting point, to at least buy us some time before the ravages of cleverer deep fakes run wild.

That extra time allows us to build a stronger collaborative intelligence, which draws on the insights and ideas of people throughout the coalition for integrity. These insights and ideas need time to be evolved and molded into practical solutions.

However, I anticipate not just a collaboration between human minds, but also a rich collaboration involving AI minds too.

A collaboration of minds – humans and AIs (Credit: David Wood via Midjourney)

Critically, AI systems aren’t just for ill-intentioned people to use to make their deep fakes more treacherous. Nor are they just something that can power real-time fact-checking, important though that is. Instead, they are tools to help us expand our thinking in multiple dimensions. When we use them with care, these systems can learn about our concerns regarding worse cases of deep fakes. They can consider multiple possibilities. Then they can offer us new suggestions to consider – ways probably different from any I’ve listed above.

That would be a striking example of beneficial artificial intelligence. It would see deep fakes defeated by deep benevolence – and by a coalition that integrates the best values of humans with the best insights of AIs.

Let us know your thoughts! Sign up for a Mindplex account now, join our Telegram, or follow us on Twitter. 

The Biggest Crypto Narratives of Q2 2024

Posted on by Werner

As we enter the second quarter of 2024, the cryptocurrency market is gearing up for what is expected to be an explosive phase of the 2024 bull run. 

The narratives that drove the market in the previous months have evolved, and new trends are emerging, which will force crypto holders to take a long hard look at their portfolios and probably make some changes.

Let’s take a look at the hottest sectors in crypto for Q2 2024 and what to expect.

Please note, nothing in this article should be considered financial advice and any readers planning on investing should do their own research. Crypto assets are highly volatile in price and you could lose everything if you invest. 

Bitcoin Ecosystem

Surprisingly, some of the most cutting-edge developments are taking place on the world’s original crypto chain, which has been known to adapt to new tech with great difficulty. 

The Bitcoin ecosystem is seeing significant development after its Taproot upgrade enabled DeFi and smart contract development. The last year has been up-only for smart contract-powered layer-2 networks like Stacks, and of course the creation of Casey Rodarmor’s Bitcoin Ordinals protocol, which has now led to over 60 million inscriptions and thousands of Ordinal projects. 

These projects are bringing new functionality to the Bitcoin blockchain, enabling new decentralized applications and unique digital assets. Rodarmor’s latest project Runes kicks off next month and promises to solve a lot of the congestion issues caused by BRC20 tokens. 

Memecoins

With Bitcoin is in price discovery mode post-$70k, memecoin mania has broken out all over crypto and shows no signs of abating, 

They continue to capture the attention of crypto traders that resemble a cult, with animal-themed projects like Pepe, Dog Wif Hat (WIF), Bonk, Shiba Inu, Ballz, and Brett making millionaires (and ‘brokies’) of degen traders. While these projects all lack fundamental value, they can generate significant short-term gains and serve as a gateway for new users entering the crypto space who don’t understand the difference between zero-knowledge and optimistic rollups and frankly don’t care. All they care about is whether to ‘ape’ (buy) or ‘jeet’ (sell). 

Layer-1 Chains

One of the key sectors to watch is the Layer-1 blockchain space. While established players like Ethereum, Cardano and Solana remain relevant, newer entrants such as TON (the Telegram chain), Avalanche, Arweave, Fantom, Near, and Sui are gaining traction with various narratives. 

These platforms are attracting attention due to features such as TON’s bullish tokenomics, Arweave’s decentralized storage solutions, Fantom’s high-performance blockchain, Near’s focus on AI (Fantom recently featured on a Jensen Huang-led panel at a major AI conference last week), and Aptos and Sui’s groundbreaking Move programming language, inherited from the defunct Facebook currency project Diem. 

Layer-2 Chains

Another notable trend is the rise of Layer-2 solutions, particularly those built on Ethereum. Ethereum’s recent Dencun upgrade that introduced Proto-danksharding (EIP4884) was a huge boon to Layer-2 solutions because it has now dramatically lowered their transaction fees, opening up new applications. 

Optimism stands out as a promising project. Coinbase’s Base blockchain is built on top of its OP Stack, and as Base begins to gain adoption, Optimism is expected to see increased usage and value capture. Base’s royalty payments fund them directly, and the prestige of providing the foundation of the technology for the Coinbase chain helps raise their profile.

Zero-knowledge proof rollups, supposedly technologically superior to optimistic rollups, continue to accumulate market share, and with the recent launch of StarkNet and others like Polygon Era and ZkSync building like mad (the latter expected to launch and airdrop its token later this year) the Layer-2 wars are far from over.

Credit: Tesfu Assefa

DEXs

This week it was announced that Coinbase would go to court with the SEC, while centralized exchange KuCoin was charged by US authorities for a litany of serious financial crimes such as breaking Anti-Money Laundering regulations. With many centralized exchanges still not offering sufficient KYC regimes, expect this housecleaning to continue to clear the way for TradFi firms to enter the market. 

This means that the flight to self-custodial solutions continues, having started with the collapse of FTX and others in 2022. In particular, decentralized exchanges (DEXs) are also poised for growth, with ‘perpetual DEXs’ like GMX and Aveo leading the charge. These platforms offer users the ability to trade leveraged positions without centralized intermediaries. 

Traditional DEXs, in particular Solana-based ones such as Jupiter, Orca, and Cosmos-based ones like Raydium and Astroport, are also expected to cash in on increased trading activity brought about by the memecoin and AI crypto narratives.

DePIN and AI

The AI and decentralized physical infrastructure (DePIN) sectors are closely intertwined and present significant opportunities. Projects like Bittensor and Akash Network are at the forefront of decentralized AI hardware and cloud computing, respectively. Other notable projects in the DePIN space include AIOZ, and Render, which focus on various aspects of decentralized infrastructure. 

Crypto AI pioneer SingularityNET is also expected to continue its impressive growth this year as its ecosystem and marketplace expands and likely takes on some of its peers as new partners.

Crypto Gaming

Crypto Gaming is another sector that can finally surge back to investor awareness after two years in the doldrums. Projects like ImmutableX, Injective and Beam are building the infrastructure necessary to support the next generation of blockchain games, by offering features such as gas-free NFT minting, custom-tailored gaming blockchains, and strong partnerships with established gaming companies.

Real-world Assets (RWAs)

If you follow any crypto discussions on social media and news outlets, you’ll know that RWAs have been touted as a massive new market for crypto, after BlackRock Larry Fink’s espoused the benefits and future potential of the technology. 

Real-world assets (RWAs) are increasingly being tokenized on the blockchain, and several projects are charging forwards in this sector. Ondo, Centrifuge, and Pendle are some of the key players in the RWA space, offering a range of financial products and services, including borrowing, lending, and yield generation.

Cross-chain interoperability is becoming increasingly important as the blockchain ecosystem matures. Projects like THORChain are building the infrastructure necessary to facilitate seamless asset-transfer across different blockchains, enabling greater liquidity and user adoption.

Conclusion

Q2 2024 will almost certainly be marked by some explosive volatility, as forces such as the Bitcoin Halving, a potential Fed reduction of interest rates, and the run-up to the 2024 US Presidential Elections continue to shape market behavior. 

It is essential for investors to remain informed and adaptable, and maintain a strong understanding of their risk exposure and what they’re willing to lose. By understanding the key narratives and projects driving the market, investors can position themselves to capitalize on the potential gains. Hold on to your hat, or sell your dogwifhat, it’s going to be a wild ride.

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Revolutionizing Digital Archives: ChatGPT Integration in the Latest Version of the Internet Archive’s TV/News Archive | Mindplex Podcast – S2EP14

Posted on by Mindplex

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Coinbase Report: Are Crypto AIs a Mirage Or For Real?

Posted on by Werner

Artificial Intelligence (AI) has been making rapid strides in recent years, with breakthroughs like ChatGPT, Midjourney and Claude capturing the public imagination. At the same time, the world of cryptocurrency and blockchain technology is expanding, vying for the attention of a still-young digital economy. Can these two cutting-edge fields co-exist and aid each other’s evolution? The question presents both exciting opportunities and complex challenges.

A new report by Coinbase, a leading US-based cryptocurrency exchange, which also launched the surging Base layer-2 network, delves into the current state of the crypto-AI landscape. The report highlights that while there is significant potential in the overlap between technology’s two brightest sectors, the path to widespread adoption is not that straightforward. Different sub-sectors within this intersection have vastly different opportunities and development timelines.

One key observation is that decentralization alone is not enough for an AI product to succeed in the crypto space. It must also reach feature-parity with centralized alternatives. Crypto-based AI solutions must offer compelling advantages beyond just being decentralized.

The report also suggests that the value of AI tokens may be overstated due to the current hype around AI. Many AI tokens may lack sustainable demand-side drivers in the short to medium term, despite the excitement surrounding them.

Key Trends in Crypto AI

Open Source Models Carry On

The AI sector has a thriving open-source ecosystem, with platforms like HuggingFace.co hosting a wide range of publicly-available models. This open-source culture coexists with a competitive commercial sector, ensuring that non-performant models are quickly weeded out.

Credit: Coinbase’s Institutional Market Intelligence Report, March 6, 2024

Smaller AI Models Gain Traction

Despite this, smaller AI models are increasing in quality and cost-effectiveness. Fine-tuned open-source models can even outperform leading closed-source models in certain benchmarks. This trend, combined with the open-source culture, enables a future where performant AI models can be run locally, offering a high degree of decentralization.

AI Integrations Strongly Benefit Existing Platforms

The report notes that existing platforms with strong user lock-in or concrete business problems are well-positioned to “disproportionately” benefit from AI integrations. 

  • For example, GitHub Copilot‘s integration with code editors enhances an already powerful developer environment. Similarly, embedding AI interfaces into various tools like mail clients, spreadsheets, and CRM software are natural use-cases for AI.
  • In such scenarios, AI models augment existing platforms rather than creating entirely new ones. 
  • AI models that improve traditional business processes internally often rely on proprietary data and closed systems, making them likely to remain closed-source.

Hardware and Compute Trends

In the AI hardware and compute space, there are two distinct trends:

One is shifting computation from training to inferencing: with more models now available, the focus moves towards making queries to these already-trained models. This trend favors platforms that can reliably run production-ready models securely.

A second, related trend is that the competitive landscape around hardware architecture is evolving, with new processors from Nvidia, Google, and Groq potentially shifting cost dynamics in the AI industry. Cloud providers that can quickly adapt, procure hardware at scale, and set up associated infrastructure stand to reap the rewards of these developments.

Credit: Tesfu Assefa

Crypto’s Role in the AI Pipeline: Four Stages

The Coinbase report next examines crypto’s potential impact on four stages of the AI pipeline: 

1) data collection and management

2) model training and inferencing

3) output validation

4) tracking

1) Data Collection and Management

Historical blockchain data is a rich source of training data for AI models. However, commercial models tend to use proprietary datasets, posing challenges for decentralized data marketplaces, which need to compete with both open-source data directories and corporate silos.

Decentralized storage also faces hurdles in the AI industry. While decentralized storage can offer potential cost savings, it currently lacks the tooling, integrations, and predictable costs of mature cloud systems. Regulatory and technical challenges around sensitive data storage on decentralized platforms remain significant barriers.

2)  Model training and Inferencing

In the model training and inferencing stage, decentralized compute solutions like Render and NuNet aim to leverage idle computing resources to provide an alternative to centralized cloud providers. While some projects have seen increased usage, long-term success faces strong competition from established players. Technical limitations like network bandwidth constraints also pose challenges for decentralized compute networks.

3) Output Validation

Validating AI model outputs, and ensuring trust is another area where crypto-based solutions are being explored. However, the complexity of model benchmarking and the increasing feasibility of running models locally on consumer hardware raise questions about the demand for trustless inferencing solutions.

4) Tracking

Finally, the importance of tracking AI-generated content and proving online identity is growing. While decentralized identifiers and on-chain data hashes can help address these issues, centralized alternatives like KYC providers and AI watermarking techniques are also being developed.

Trading the AI Narrative

 Growth in the past year (Credit: BanterBubbles.com)

Despite the challenges, AI tokens have outperformed major cryptocurrencies and AI-related equities in recent months. The report suggests that AI tokens benefit from strong performance in the crypto market and in the AI industry, leading to upside volatility even during bitcoin drawdown periods. Hype drives demand, and investors will be piling in for some time to come. 

However, the lack of clear adoption forecasting and metrics has enabled speculative trading that may not be sustainable in the long run. Eventually, as in every crypto cycle, price and utility will need to converge, either through rising use-cases or falling prices.

Looking Ahead

The marriage of AI and crypto is still in its very early stages, and is likely to evolve rapidly as the broader AI sector develops. A decentralized AI future, as envisioned by many in the crypto industry, is not guaranteed. Crypto-based solutions are technically feasible, but to drive adoption they must provide meaningful advantages over centralized alternatives.

The AI industry itself is undergoing swift changes, fighting more and more headwinds as public opinion often turns against it. Therefore it is crucial to navigate this space carefully. Deeper examination of how crypto-based solutions can offer substantially better alternatives, or at least a clear understanding of the underlying trading narrative, is essential for investors and entrepreneurs alike.

As the AI and crypto landscapes continue to search for a sustainable symbiosis, ongoing research and experimentation will be vital to unlocking the potential of this area while meeting its challenges. 

The future of decentralized AI is still being written, and it will be shaped by the ingenuity and perseverance of the innovators working at the forefront of these transformative technologies.

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Bitcoin Ordinals: A Quick Guide

Posted on by Werner

Non-fungible tokens (NFTs) used to be the sole domain of Ethereum and other smart contract networks like Cardano and Solana. During the 2021 bull run, the world caught crypto JPEG fever thanks to collections like Crypto Punks, Bored Ape Yacht Club (BAYC) and 2024 darling Pudgy Penguins (now in a Walmart near you), and Ethereum was the infrastructure that captured most of the value. 

In early 2023, a new challenger kicked open the saloon doors, making a crazy entrance into the Wild West of crypto: Ordinals. The crazy part comes with that it lives on the Bitcoin blockchain, which is notoriously slow (only seven transactions per second) and with a hardcore Bitcoin maxi community strongly resistant to any change. 

Despite this, it’s been up only for Bitcoin Ordinals, as over 64 million have been minted by the time of this article. 

What are Bitcoin Ordinals? 

Ordinals in their current form were introduced by Bitcoin developer Casey Rodarmor on 21 July 2022 with the publication of his Ordinal Theory paper.

Bitcoin Ordinals are a way of assigning a unique identifier to each satoshi (sat), the smallest unit of Bitcoin, based on the order in which it was mined. By assigning an ordinal number to each sat, it becomes possible to create unique, distinguishable assets on the Bitcoin blockchain. This means that every single sat can be individually tracked and associated with specific data, such as images, videos, or other digital artifacts. 

According to Rodarmor, Ordinals’ genesis can be traced back to Satoshi Nakamoto’s creation of the Bitcoin blockchain in 2009. That means that especially early Ordinals have a historical significance within the blockchain’s timeline. He also noted that the concept of ordinals was independently discovered multiple times, predating the NFT boom by nearly a decade, most notably:

  • Litecoin creator Charlie Lee’s 2012 proposal on the Bitcoin Talk forum to integrate proof-of-stake using the ordinal algorithm
  • jl2012’s introduction of a decimal notation scheme that mirrored key features of ordinals.

Although neither proposal was fully realized, they underscore the enduring interest and potential of ordinals within the Bitcoin community, long before their recent surge in popularity.

Rodarmor wrote,

These independent inventions of ordinals indicate in some way that ordinals were discovered, or rediscovered, and not invented. The ordinals are an inevitability of the mathematics of Bitcoin, stemming not from their modern documentation, but from their ancient genesis. They are the culmination of a sequence of events set in motion with the mining of the first block, so many years ago.

How do Bitcoin Ordinals work?

Creating a Bitcoin Ordinal involves ‘inscribing’ data onto a specific sat, hopefully the rarer the better. This is done by embedding the inscribed data into the witness data of a Bitcoin transaction, using the ordinal number of the sat as a reference point.

To understand how this works, let’s break down the technical details:

  1. Ordinal numbers: Each sat is assigned an ordinal number based on its position in the blockchain. The first sat in the genesis block is assigned the number 0, the second sat is assigned 1, and so on. This numbering scheme continues sequentially throughout the entire Bitcoin blockchain.
  2. Inscribing: An inscription is the process of embedding data (such as an image or video) into a Bitcoin transaction using the ordinal number of a specific sat. This is done by including the data in the witness data of a taproot script-path spend.
  3. Taproot and SegWit: Bitcoin Ordinals leverage comparatively new upgrades to the Bitcoin protocol, specifically Taproot and Segregated Witness (SegWit). These provide more flexibility in the types of transactions that can be recorded on the blockchain, making it possible to embed larger amounts of data.
  4. Transfers and ownership: Once an inscription is made, the associated sat can be transferred or sold just like any other Bitcoin. The ordinal number and associated data remain linked to the sat throughout its lifetime on the blockchain.

Credit: Tesfu Assefa

Rodarmor Rarity Index

According to the Rodarmor Rarity Index, created by Casey Rodarmor, the developer of Ordinal Theory, satoshis can be classified into different categories based on their rarity. About 99% of sats are considered Common Sats. 

Uncommon Sats are the first sat of each newly mined block, occurring roughly every 10 minutes. Rare Sats are the first sat of the block mined after a Bitcoin network difficulty adjustment, which happens every 2,016 blocks or about two weeks. Epic Sats are the first satoshi mined in the block immediately following a Bitcoin halving event, occurring every 210,000 blocks or roughly four years. 

Legendary Sats are the first satoshi mined when a difficulty adjustment and halving event coincide, which will happen only once every 24 years, with the first instance scheduled for 2032. Finally, the Mythic Sat is the first-ever satoshi mined by Satoshi Nakamoto in the genesis block in 2009.

Magic Eden Rare Sats

Magic Eden drive most Ordinals sales, and have created their own version of the Rodarmor Rarity Index. Let’s go over it: 

  • Nakamoto Sats: Highly sought-after sats mined by Bitcoin’s pseudonymous creator, Satoshi Nakamoto.
  • First Transaction Sats: Sats originating from the first-ever Bitcoin transaction on January 12, 2009, when Satoshi Nakamoto sent 10 Bitcoins to Hal Finney.
  • Palindrome sats: Sats whose numbers can be read the same forwards and backwards (e.g., 16661 or 23832), adding a layer of rarity and curiosity.
  • Vintage Sats: Sats mined within the initial 1,000 blocks of the Bitcoin blockchain, marking the dawn of Bitcoin.
  • Pizza Sats: Sats from the iconic transaction on May 22, 2010, where a programmer paid 10,000 Bitcoins for two Papa John’s pizzas worth $27 at the time, and thereby created a monetary value for BTC.
  • Block 9 Sats: Some of the oldest sats in circulation, mined in one of the earliest blocks and offering a tangible connection to Bitcoin’s beginnings.
  • Block 78 Sats: Sats from the block mined by Hal Finney, marking the first instance where someone other than Satoshi Nakamoto (or is it???) contributed to the blockchain’s growth.

The Essential Ordinals and Rare Sat Tool Case

Some of the best tools for exploring the world of Ordinals include Ordpool.space for tracking Ordinals in the mempool, Liquidium.finance for Ordinals DeFi, and Ordiscan.com for checking your wallet for assets like runes. 

Geniidata and Ord.io are popular Ordinals explorers, while Sating.io and Automated Sat Hunter by Deezy Labs helps you scan your wallet for rare sats. For launching your own Ordinals project, consider Ordzaar, and for inscribing data, Ordinalsbot is the go-to. 

Conclusion

Bitcoin Ordinals represent a significant development in the evolution of Bitcoin, enabling the creation of unique, NFT-like digital assets native to the Bitcoin blockchain. While the concept is still relatively new, it has the potential to unlock a wide range of use cases and drive innovation in the Bitcoin ecosystem, which includes anything from digital art to gaming to even digital identity. With Bitcoin layer-2 chains also improving in leaps and bounds, the future looks extra-ordinally bright (sorry, couldn’t resist!) for this new digital asset class. 

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Can AI Aid in the Recovery Of Lost Bitcoin?

Posted on by Werner

Every time Bitcoin hits a new all-time high, we hear that about ‘about 20%’ of the Bitcoins minted are lost, never to be recovered, with some seriously sob stories thrown in for good measure. They were lost for various reasons, and more continue to go missing, albeit less often these days. Most of those missing Bitcoins have been lying dormant for several years. In Bitcoin’s early days, stashes of Bitcoin weren’t seen as the honeypots they are today, and people got careless, only to pay the ultimate price of losing their BTC. Now, with the age of AI upon us in 2024, can new technologies help retrieve those missing fortunes? 

Careless Early Miners

In the early years of blockchain, from 2009 to 2014 or so, some individuals had found a hobby using spare PCs to mine Bitcoin. This wasn’t terribly lucrative in fiat terms at the time, but many of those miners racked up what would now be enviable collections of dozens, hundreds, or thousands of Bitcoins. By now, most of us have heard about the missing hard drives that contain many millions of dollars worth of Bitcoin. These days, one solitary Bitcoin is worth a tidy sum in fiat money, and accumulators speak of ‘stacking Sats’ (1 SAT = 0.00000001 BTC) rather than accumulating full Bitcoins.

Recovery Efforts

Have any of those stray Bitcoins been recovered? Yes, a small percentage of them have, and there is hope that state-of-the-art decryption techniques and the latest GPUs can be put to use to reclaim more of them. Companies have been set up to assist people in recovering missing Bitcoin wallets, and these efforts have seen some modest success in cases where there is at least a bit of a trail that could lead to the missing Bitcoins.

Bitcoin cryptography is strong. A private key represents a unique number between 1 and 2 to the power of 256. That’s more than the total number of atoms in the universe. With current technology, a brute force attack to test a colossal number of potential keys until landing on the right one would take millions of years.

Is it hopeless? Is it not even worth trying? That depends. If the owner of missing Bitcoins has any hints at a seed phrase, records of where it may have been transferred to or stored, or a physical storage device, that could greatly cut down the time it would take to get to a positive result.

AI to the Rescue?

Artificial Intelligence has been a hot topic of conversation for a while now, and cryptocurrency is not immune from AI influence. When it comes to cracking a Bitcoin wallet, the brute force method will be futile on its own, but AI models are being developed that can drastically shorten the time it takes to crack a private key. 

With machine learning and the most powerful GPUs, patterns can be identified within vast collections of data that can significantly bring down the time it takes to uncover encryption keys.

Enter PassGPT, a cutting-edge password guessing AI model that could be the saviour that unlocks your lost millions. Built on OpenAI’s GPT-2 architecture and trained on millions of exposed credentials, PassGPT has a unique edge over other password-guessing tools. By using a technique called progressive sampling, it constructs passwords one character at a time, making it 20% more effective than even the most advanced GAN models.

But PassGPT isn’t just a one-trick pony. It can analyse password strength, identify patterns, and even guess passwords in multiple languages. And it can come up with new passwords that aren’t even in its training data.

So, how could this help you recover your lost Bitcoin? By adapting PassGPT to focus specifically on Bitcoin wallet passwords and feeding it data on common password patterns used by crypto enthusiasts, its effectiveness could be supercharged.

Of course, this technology raises some security concerns, but when used responsibly, it could be a lifeline for those who have lost access to their Bitcoin due to a forgotten password. As generative AI continues to evolve, solutions like PassGPT could become an invaluable tool in the ongoing challenge of balancing security and accessibility in the world of cryptocurrency.

Side-Channel Attacks on Hardware Wallets

Hardware wallets are a common and extremely secure way to store private keys offline. When used judiciously and prudently, they work very well – and best practices should be followed to ensure that private keys are backed up in another separate location, just in case the device goes missing or the owner becomes incapacitated. If an older or less sophisticated hardware wallet has become inaccessible, a side-channel attack offers a glimmer of hope.

A side-channel attack is a method of exploiting any physical characteristics of a hardware wallet that can be detected via electronic sensors. Characteristics including timing, power consumption patterns, and electromagnetic and acoustic emissions which can sometimes reveal enough information to obtain fragments of the PIN code to access the wallet or crack the private keys. Although only fragments may be uncovered, they can still drastically reduce the time taken for cracking tools (including AI and machine learning) to search for the private key.

Technology is advancing all the time, and different hardware wallets will have different levels of vulnerability to side-channel attacks. One of the most well-known hardware wallet makers, Ledger, claims that its wallets are immune to such attacks, so mileage of side-channel attacks may vary. Ledger’s main competitor, Trezor, also claims that crypto functions have been re-written by their cryptography professionals to eliminate such vulnerabilities. Additional measures such as ‘secure elements’, which ensconces the private key permanently inside a computer chip, also makes breaking cold storage encryption near impossible. 

Credit: Tesfu Assefa

Limitations of Silicon

The silicon computer chips that power all of our digital devices have progressed at an astounding rate over the years, roughly in line with Moore’s Law. Taiwan Semiconductor and Samsung are planning to produce 1.4-nanometer chips by around 2027. These chips will lead to some astounding AI performance, but we are getting awfully close to the physical limits of silicon, and we will have to seek other technologies for computing power to continue advancing beyond silicon.

The Quantum Solution/Threat

Currently lurking in the waiting-room of the future is quantum computing. Right now, it’s cumbersome, expensive, and is years from being available commercially, but boy can it compute. It has been expected that quantum computers will be able to compute 158 million times faster than the most advanced existing silicon-based computer.

Researchers at the Centre for Cryptocurrency Research and Engineering of Imperial College London have calculated that a quantum computer with 1500 or more error-corrected qubits will be able to crack a Bitcoin private key. IBM has published a roadmap where they reckon computers with thousands of error-corrected qubits will be a reality by around 2029.

Opposingly, at the popular hacking news website, Hackernoon, they estimate that it would still take a quantum computer 10³² years of a brute force assault to hack Bitcoin. Some developers are proposing a Bitcoin encryption upgrade to ensure quantum resistance, but that would likely require at least a soft fork to implement.

Conclusion

The possibility of AI and quantum computing helping to retrieve lost Bitcoins are very exciting to some people, but threatens to destroy the value of Bitcoin, since the available supply could swell by a few million BTC, especially if they crack Satoshi’s wallet. The biggest fear is quantum computing though, and it’s good to see Bitcoin core devs putting contingency plans in place. 

Till then, good luck to the likes of James Howells, who has been trying to retrieve a hard drive with 8,000 Bitcoin on it for over a decade. That’s around $560 million right now. 

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