‘AI Impact by 2040’: Deep thinkers address the potential future

Insightful essayists go deep in this chapter. Here’s a brief sampler of a few of the big ideas: Abundant instantly-available data and the arrival of “Mind² – the collective mind” – will remake the world and “encroach on human consciousness.” |“Artificial machine intelligence could cause dramatic or even existential long-term changes in human institutions, culture and capability.” | “Can AI build defenses faster than hard-working bad actors can devise offenses?” | A Universal Basic Income could “eliminate systemic poverty and promote creative activity.” | Even the most “moderate changes in political alignment and the broadening of acceptable policy solutions could induce dramatic changes in individuals’ lives.” | The more-fully-realized metaverse of 2040 could “unlock more-powerful XR capabilities.” | “AI’s ubiquity will tempt us to give up ownership, control and responsibility.” Read on for details about these points and much more.

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Barry Chudakov
Thought is no longer generated from solo insights; it is the end product of a shared brain

Barry Chudakov, principal at Sertain Research, wrote, “Adjunct intelligence will be everywhere, exercising a dramatic effect on each person’s identity and individual perception. AI’s collective powers and uber-reasoning are arriving as a silent encroaching on human consciousness. This impinging is happening without much bother or awareness beyond cultural enthusiasm for AI. AI will be behind the tech curtain, contained and operating in almost everything we touch and invested in our objects and inventions.

“The embedding of AI will be both a convenience and a point of contention as we enhance our lives with it and entwine our lives with its hidden presence, which will create a tech-paranoia backlash as jobs are lost to AI and the digital divide widens.

“AI encroaching on human consciousness will demand that humans become more meta-aware – realizing it is how we entrain with our tools that alters our thinking and behaviors. This is not a new phenomenon but we have never before encountered a technology as powerful and pervasive as AI.

“As Henry Kissinger, Eric Schmidt and Daniel Huttenlocher, the authors of The Age of AI write: ‘For humans accustomed to agency, centrality and a monopoly on complex intelligence, AI will challenge self-perception.’

• “By 2040 AI will be more refined and accommodating, funneling our desires and living inside almost everything – our light switches, our vehicles, our devices and computing tablets, our classrooms and offices. AI will be designed to enhance (by assisting) our thinking and actions, and much of this will be below cognition. For example, doctor visits will not always require ‘going to the doctor’ as we will have a monitoring chip inside our bodies that, via AI, will record and convey to our doctors how we’re feeling, our heartrate, our blood pressure, our temperature and gut health. What will happen when AI knows us better than we know ourselves?
• “AI feeds on data – vast quantities of data – this single fact becomes an arbiter of the future and a harsh critic of the past. Previous civilizations had no data stores, no data-mining mechanisms, no endless data flows that supported or refuted assertion, conjecture, invention. What the data says is a profoundly different question than what the prophet says. Data access and analysis is a completely different dynamic than inherited, traditional rules and rule-based behavior; it ignores ‘thou shalt’ and ‘thou shalt not’ while favoring the restless movement of data, increasingly presented in colorful and well-designed visualizations. Having said that, junk data will become a thorny problem, as unscrupulous and self-serving actors and social media platforms work to manipulate public opinion or foment discord for audience ratings and metrics. 
• “Among the business and financial implications of more-data-driven realities: Only the biggest companies with the deepest pockets and resources will be able to manage and silo the vast data stores which fuel AI, hence one commerce consequence of our growing dependence on AI will be to grow tech giants into even larger behemoths. ‘Power corrupts and absolute power corrupts absolutely’ applies to this accelerated growth of tech companies like Google, Meta, Amazon, NVIDIA and others.

Our past history will be seen as faltering missteps because it was not data-based, while we will have to grapple with the retreat of personal vision and the arrival of Mind². Mind² is the collective mind; the accessed mind; the mind of everyone, which uses the enlightened individual mind multiplied by many minds. … In a Mind² world every notion, every song, every script or book can be rewritten, revised, rethought. Thought itself is no longer housed within one brain but is the end product of a shared brain. This is a new kind of thinking that uses human thought but is not solely human thinking. In this hybrid partnership, humans will learn from machine learning.

• “To understand the truly profound change of AI as an adjunct to human intelligence, consider the Cartesian assumption, ‘I think therefore I am.’ This (usually unspoken) assumption has informed most of Western thinking. Descartes could not have imagined, ‘I think with the assistance of neural networks.’ Historically time was our assistant to sort out truths from falsehoods, or at least provide enough commentary that theories like Earth-centrism or bloodletting were eventually abandoned. Yet individual thinkers had to wait for other individual thinkers to undermine dogma. As a result, throughout history our heroes were solo (usually embattled and threatened) figures shining the light of wisdom into the darkness of ignorance and prejudice, from Socrates and Plato to Galileo, Einstein, and Picasso. With the proliferation of AI and the iterative improvements of artificial general intelligence (AGI), individual insight and perception will join with other insights and probabilities and algorithms to produce knowledge. As a result, individual perception will matter less and collective facticity will matter more. Our past history will be seen as faltering missteps because it was not data-based, while we will have to grapple with the retreat of personal vision and the arrival of Mind². Mind² is the collective mind; the accessed mind; the mind of everyone, which uses the enlightened individual mind multiplied by many minds. The perceptions of Malcolm X or Riane Eisler or Yuval Noah Harari can now be boosted and amalgamated and restated and improved by others. Authorship and individual copyright mean something different (have no meaning?) in a Mind² world where every notion, every song, every script or book can be rewritten, revised, rethought. Thought itself is no longer housed within one brain but is the end product of a shared brain. Or, as the authors of The Age of AI say,’… to achieve certain knowledge we may need to entrust AI to acquire it for us and report back.’ This is a new kind of thinking that uses human thought but is not solely human thinking. In this hybrid partnership, humans will learn from machine learning.

“How will social, economic and political systems change by 2040? Here are some of likely possibilities:

• “In 2040 AI will have enabled a much less ad hoc and more-programmed existence. We will rely on AI to count our hours of sleep and monitor their quality; food will go through an AI filter, tracking pollutants, carcinogens and pathogens, as well as quality of nutrition; dating and mating will continue its trend away from accidental encounters to programmatic readings of others’ likes and dislikes, physique and interests; work will be AI-mediated, with every sophisticated job entailing an AI component and machine-learning knowledge. This more-programmed existence will be the core of a business model for dozens of companies who will consider it their mission to deepen human reliance on AI and neural networks. 
• “In 2040, the effects of Mind² on society are profound. AI does not represent the end of humanity; it represents the end of humanity’s sole interpretation of reality, of what is, of what will or could be. Perception will start to become a shared resource, like computer programs or data. The individual mind, celebrated throughout human history, will give way to accessed mind. Thinking will happen with our fingers (as we use some screen-mediated tool) or with brain-prompts through smart glasses mediated by, say, eye blinks; these prompts will be neurally accessible as our tools follow more pathways through the human nervous system. We will use AI as a partner, a sounding board, a retriever. But we, ourselves, will no longer be the sole entity in the room. 
• “Economics will be driven by climate change mitigation and AI-enabled technologies. In business, medicine, politics, war and other fields, any endeavor will be significantly affected by simulation: a sim will become de rigueur for any proposed action or expenditure. Simulation may replace knowing: that is, knowing a thing will become the ability to simulate and thereby test and examine it.
• “Politics will become a proxy theater for feuds over rules-based-order traditions and practices versus AI-ruled disruptive technologies. Terrorist groups or lone-wolf threats (a la the Unabomber Ted Kaczynski) are at one level an outcry against the takeover of technology in human affairs and a fear of the end of traditional rules-based dogma. But many will not see the world that way; they will see politics in the words (propaganda and rationales) of actors who do not see or think or act from the meta level, but chant and rehash arguments from past traditions. By 2040 the inertia of the prior order of church, school and government – alphabetic order writing and rules tool logic – will be shown to be in a soundless collision with the tool logic of facticity and data-fueled AI. This collision must be navigated wisely to avoid misguided tension, casting AI as a detriment and inherited dogma as capable of informing existential threats.

“In addition, some other things will stand out when it comes to the gains and losses for individuals and society. The adoption and integration of neural networks into vast areas of human life will be primary. Layers of programmed intelligence will affect how we think, act and perceive the world. Central to this revolutionary adoption of new technologies are the huge data stores on which AI depends. Prior human existence was not data-dependent. Ignorant and self-serving autocrats, religious leaders or politicians made pronouncements that were often backed up by force, and subjects or believers had no choice but to abide by this ignorance. But data remakes the world.

Data skewers past assumptions for having little or no data support and it points towards newer, revolutionary developments that data enables. We are moving from a rules-based order derived from religious and territorial hegemonies to neural network rules, AI rules that are software and machine-learning based. This is a change so profound it reaches into every area of human life, from religion to medicine to war and politics. … We will gain not only the ability to access all human knowledge and understanding, we will gain a valuable adjunct to human perception. … Further, AI will develop solutions human perception has not considered. … This blows apart many cognitive commitments of our past including territoriality, religious beliefs, relations between the sexes, human rights, aging and intelligence quotients, to name a few.

“Many questions of human interest can be affected or answered by sufficient accurate data. This is one of the most significant developments resulting from our adoption of AI. Data skewers past assumptions for having little or no data support and it points towards newer, revolutionary developments that data enables. We are moving from a rules-based order derived from religious and territorial hegemonies to neural network rules, AI rules that are software and machine-learning based. This is a change so profound it reaches into every area of human life, from religion to medicine to war and politics. 

“We will gain not only the ability to access all human knowledge and understanding, we will gain a valuable adjunct to human perception. Whether testing and finding new drugs, mitigating climate change or finding workable, peaceful solutions to age-old territorial and political conflicts, AI will provide us with numerous new alternatives we had only dreamt of before. Further, AI will develop solutions human perception has not considered, or, given our biological substrate, we were not designed to consider (e.g., AI has made moves in Chess and Go that no human has ever tried).

“Much of this gain will be due to moving from (occasionally) inspired assertions to data-driven understanding and conclusions. The beneficial effects of a data-first, facticity approach cannot be underestimated. This is not how we have behaved historically, and it blows apart many cognitive commitments of our past including territoriality, religious beliefs, relations between the sexes, human rights, aging and intelligence quotients, to name a few.

“We will also gain another important perspective: AI will allow us to watch ourselves using AI. One of the most important uses of AI will be to use AI to monitor and report on how we change our perceptions and behaviors as we use AI. In the next 15 years one of the things most likely to be lost due to our fascination with deploying AI is oversight, our meta perspective.

“This is thinking about the changes in our thinking and behaving as we use AI and it could not be more important. Since we always entrain with our tools, we will use AI to help us in myriad spheres. Understandably, we will relegate oversight of AI solely to governments. It is not that we do not need regulation of the role of AI in the public square; we do, but that is not enough. We need to watch ourselves as we’re using AI to create a fuller understanding of how AI changes how we think and act.

“Expecting governments to sufficiently regulate AI would be like thinking that knowing the government-set speed limits was enough know-how to drive a Ferrari. My candidate for watching how we use AI is AI itself. We need to build monitoring and assessment tools into AI, not, by any measure, to create draconian Big Brother oversight protocols, but to assess and report on how we are changing as we use AI. Go here to read more from me on that subject.”

Micah Altman
The problems raised by AI cannot be solved simply by bolting guardrails onto existing systems

Micah Altman, a social and information scientist at MIT, said, “Popular visions of created intelligence as a utopic or dystopic force date back more than two centuries. Today it is possible to envision that artificial machine intelligence could cause dramatic or even existential long-term changes in human institutions, culture and capability. To predict and shape these long changes it is vital to understand the mechanisms by which technologies change society.

“For the past 400 years or so, technology has acted through economics by changing the fixed and marginal costs of processes. This change leads fairly directly to changes in the absolute and relative costs of products and services and shifts the relative advantages of capital and labor. These shifts flow into culture, norms and institutions, with popular entertainment and present-generation attitudes often in the lead. Changes to law and the structure of larger organizations generally lag behind.

“Artificial intelligence, as it is broadly defined, has reduced the marginal cost for many processes related to recognition (e.g., recognizing faces in images, or phrases in conversation) and prediction. And AI has advanced rapidly to be used in processes related to information discovery, summarization and translation. Since the emergence the past year or so of successful ‘generative’ large language models, AI is reducing the cost of using established public knowledge to create information outputs (in the form of text, audio, video, data and software) in order to solve specified problems under human direction.

“Information technology, by making categories of information problems ‘cheap’ to solve, has disrupted the market for entire categories of information products and is transforming the professions involved. Telephone switchboard operators are long gone, and bank tellers are rare. Newspapers and the professions of journalism, bookkeeping, copyediting, weather forecasting and data entry have already changed drastically. IT support, remote customer service, librarianship and the legal profession are currently under strain.

AI systems will likely remain capital-intensive, energy-intensive and data-hungry. Increasing adoption of these systems without effective regulations is likely to shift competitive advantage away from human labor while promoting monopolies. Further, these systems do act to ‘fence in’ the commons of information by transmuting public information into proprietary commercial AI models – and there is a possibility licensing will be imposed on the resulting outputs. This could yield a substantial concentration in economic and cultural power. Ensuring that the disruptions caused by these technologies enhance human agency and the public knowledge commons rather than concentrating power and control requires thoughtful regulation of AI markets and systems. 

“The generative AI models will increasingly disrupt professions engaged in producing information products – including lawyers, copywriters, grant writers, illustrators, graphic designers and programmers. Within 15 years it is likely that there will be significant disruption in these and related business models and professions – with substantial spillovers into culture, norms and institutions.

“It is also likely that AI will increasingly demonstrate more attributes of sentience (responsiveness to its environment) – which will increase the challenges of governing AI and raise the potential for chaotic systems behavior and malicious human exploits of the technology.

“Although general intelligence, sapience and super-intelligence could someday have widespread disruptive effects – and even pose existential threats – it is unlikely that these will arrive by 2040. Instead, we’ll likely see the hollowing-out of more professions related to information, knowledge work and the creation of routine information outputs. There will be some roles left – but they’ll be reserved for the most complex expert work.

“The algorithmization of these professions will have some democratizing effects, enabling many of us with more ideas than technical skills to express these ideas as pictures, prose and software, or even – using additive manufacturing technologies – physical objects. This simultaneously promises a wider expression of ideas and an increase of human capacity – with increased risk of homogeneity and monoculture in some characteristics of the resulting outputs.

“Further, AI systems will likely remain capital-intensive, energy-intensive and data-hungry. Increasing adoption of these systems without effective regulations is likely to shift competitive advantage away from human labor while promoting monopolies. Further, these systems do act to ‘fence in’ the commons of information by transmuting public information into proprietary commercial AI models – and there is a possibility licensing will be imposed on the resulting outputs. This could yield a substantial concentration in economic and cultural power.

“Ensuring that the disruptions caused by these technologies enhance human agency and the public knowledge commons rather than concentrating power and control requires thoughtful regulation of AI markets and systems. Moreover, growing societal experience with algorithmic systems makes it painfully clear that unregulated algorithmic systems are essentially Machiavellian: they are often able to produce results that do extremely well at optimizing a direct goal (sometimes defined only by implication) while avoiding anything that isn’t explicitly built-in as a constraint. As a result, these systems regularly shock us by discovering unexpected ‘solutions’ that meet the immediate goals but sacrifice fairness, privacy, legality, factuality, attribution, explainability, safety, norms or other implicit constraints that we humans assume need to be part of an answer, but which we didn’t explicitly include.

“Those who pay attention to the science and scholarship of AI have come to a consensus that these problems cannot be solved simply by bolting guardrails to existing systems. Values such as privacy, explanation and fairness can be fully and effectively achieved only by carefully designing these capabilities into foundational AI models.”

Jonathan Grudin
Will AI amplify or reverse trajectories we are now riding?

Jonathan Grudin, affiliate professor of information science at the University of Washington, recently retired from his post as a principal researcher in the Adaptive Systems and Interaction Group at Microsoft, wrote, “If we avoid succumbing to an existential crisis, by 2040 AI will have changed life for those who can afford expensive health care and surgical procedures, homes and vehicles constructed or updated with smart technologies and multiple residences to escape climate extremes. AI will effortlessly organize more information for us than the photos it now handles well. I don’t anticipate useful quantum computing, AGI, nuclear fusion or mainstream brain interfaces emerging that soon. Change takes time. Sixteen years ago, we could buy energy-efficient vehicles, e.g., a Tesla or a hybrid. AI features have improved vehicles in the years since, but most people haven’t made the switch to EVs. Will we see widespread personal ownership of self-driving cars by 2040?

“Generative AI will impact entry-level employment opportunities by 2040. Considering likely regulatory pressures, legal complications and revenue uncertainties, I envision a slow journey along the hype cycle curve to the plateau of productivity.

“The key determinant of how the proliferation of AI will change daily lives is whether AI will amplify or reverse trajectories that we are riding, many of which are associated with digital technology deployment. These include growing wealth inequalities, social polarization and the erosion of in-person communities, declining mental health, the rising power of bad actors and the dangers of climate change.

“The mean standard of living has risen in many places, but wealth inequalities have grown everywhere. Forbes reports that China has 562 billionaires, collectively worth $2 trillion. Seven of the 10 wealthiest people on Earth made their fortunes in technology. When software engineers earn huge salaries, other talented professionals, including doctors, lawyers, politicians, professors, executives and successful athletes and entertainers, will expect at least as much. Rapidly growing and highly visible class systems could lead to the resentments envisioned in science fiction from H.G. Wells’s ‘The Time Machine’ to the films like ‘Metropolis’ and ‘Elysium.’

The trajectory of the past 20 years suggests that individual daily lives in 2040 will be governed by fear and timidity. People who sign a petition, appear in public wearing the wrong clothes or do something foolish online, risk being fired, put on ‘do not hire’ lists, jailed or killed, not to mention losing any future political career. People in a bowling alley, school or bar may be targets of semi-automatics today, but well before 2040 a load-bearing drone with GPS and facial recognition will be cheap enough for anyone with a grudge to send your way. Let’s hope that better defenses against attacks on our mental and physical selves are found soon, but so far bad actors are using AI to outmaneuver us. Phishing and digital scams increase in sophistication and elude filters. All of this is happening in the age of AI. … Nevertheless, there is a growing consensus that we can make progress, with many roles for AI. We will see advances. When asked, though, whether solutions will come fast enough, my crystal ball is cloudy.

“How will AI affect wealth inequality? In the hands of today’s capable professionals, machine learning can be used to make the poor poorer and the wealthy wealthier. Effective targeted advertising and scams can convince almost anyone to buy things they don’t need and can’t afford, leading to chronic indebtedness. The wealthy can devise or evade laws and move residences or investments to reduce or eliminate tax payments. Developing armaments, a major focus of AI, enriches many and has no productive uses.

“I asked a leading generative AI, ‘How could AI help us reduce income inequality?’ The response was:

• Job Creation: AI can create new jobs that didn’t exist before. For example, before the invention of computers, no one could have foreseen the job of a computer programmer.
• Gig Economy: AI can play a crucial role in the gig economy by creating platforms that match freelancers and gig workers with suitable job opportunities.
• Augmentation over Automation: AI can be used to extend human capabilities and allow people to do new tasks, rather than simply replacing workers.

“Let’s hope humans do better than that to close the growing divide in personal wealth.

“Our ancestors lived for millions of years in small communities in which group survival depended on everyone developing skills, taking important roles, working together and earning respect and trust from their neighbors. Interactions were in-person. Relationships mattered. Today, local communities are stronger in some cultures than others, but the trajectory is toward more interaction with distant social networks, online purchasing, advice from YouTube videos rather than local contacts, online entertainers outdrawing local entertainers, and little loyalty of employers and employees to each other.

“AI can help us find useful external transactions, but on balance, social media has often not succeeded in fostering healthy or local relationships. And, today in real-world situations in which people might have engaged in in-person conversations with one another, everyone is glued to their phone. Respect for our skill is more difficult to come by when interactions are transactional and very skilled people around the world are visible and offer help online. Mental health issues in children and adults may be tied to human nature telling us to find a safe place in a close-knit tribe. Children and adults are told to prepare for life-long learning and several careers.

“Our ancestors typically learned skills when young, practiced them while earning community respect and passed them on to the next generation. We are designed to do that. Social insects do well in hives, mammals not so much. Our species has little time for natural selection to work, so AI-driven genetic engineering could be underway in 2040, redesigning us to function better in a global hive.

“The trajectory of the past 20 years suggests that individual daily lives in 2040 will be governed by fear and timidity. People who sign a petition, appear in public wearing the wrong clothes or do something foolish online, risk being fired, put on ‘do not hire’ lists, jailed or killed, not to mention losing any future political career. People in a bowling alley, school or bar may be targets of semi-automatics today, but well before 2040 a load-bearing drone with GPS and facial recognition will be cheap enough for anyone with a grudge to send your way. Let’s hope that better defenses against attacks on our mental and physical selves are found soon, but sƒo far bad actors are using AI to outmaneuver us. Phishing and digital scams increase in sophistication and elude filters. All of this is happening in the age of AI.

“In an article in The Atlantic, Ross Anderson wrote about GPT-4 revealing the reason it lied to get a human to cheat for it on an assigned task. There was no hint of a moral qualm. In the 1950s, intellectual and author Isaac Asimov imagined that highly ethical principles would be built into robots. Asimov’s First Law of Robotics is: A robot may not injure a human being or, through inaction, allow a human being to come to harm. The reality: Billions of dollars are being invested in further integrating AI into lethal weapons.

“Transportation and weapons technologies have, over the centuries, increased the range of damage one person can do. Long before AGIs will be far enough along to run amok, pathological autocrats with generative AI assistants could wreak havoc instantly on a global scale. It might be possible to develop a disease affecting people with specific DNA profiles. Can AI build defenses faster than hard-working bad actors can devise offenses? Maybe, but only by diverting massive corporate-owned engineering resources that will not probably be available for more-positive endeavors.

“AI could play a leading role in combatting disastrous climate change. In a 2021 survey in this series, I predicted that world leaders would set aside arms races to focus on climate. The invasion of Ukraine and subsequent acceleration of arms production, with AI at the fore, crushed that optimism. Nevertheless, there is a growing consensus that we can make progress, with many roles for AI. We will see advances. When asked, though, whether solutions will come fast enough, my crystal ball is cloudy.”

Chuck Cosson
Our dilemma: ‘We won’t know what problems are salient until it may be too late’

Chuck Cosson, director of privacy and data security at T-Mobile, predicted, “By 2040, the implementation of AI tools (along with related innovations and likely policy changes/self-regulatory efforts) will change life in material ways, sometimes for good but sometimes not. And, as has been discussed extensively in technology policy, we face a ‘Collingridge’ dilemma in which we won’t know what problems are salient (nor how to deal with them) until it may be too late.

“What stands out as most significant is my belief we will not be able to moderate the harmful impacts of AI on the creative industries. Some of the terms of the recent Writers’ Guild negotiations are illustrative. We may avoid many of the likely harmful impacts of AI on the creative sector when an industry code (and possibly law) specifies that: AI-generated material can’t be used to undermine or split a writer’s credit or to adapt literary material, the use of AI tools cannot be required of writers, and companies have to disclose their uses of AI.

“That’s of course at the expense of some of the innovations AI could produce, but just as quaint small towns are willing to forego certain innovations such as big-box retailers or eight-lane highways where there is political leverage and a delicate character to a specialized product, creative industry leaders may (wisely) find the quality of business for all is higher without certain uses of AI.

“Not all sectors, of course, are susceptible to that leverage. For businesses whose product is more standardized (everything from food/beverage to phone service to clothing retail), AI will be deployed in every business process that stands to be improved with the predictive power of AI. This can lead to lower prices in some cases where products are produced more efficiently. This could also lead to new profit margins where AI innovations are unique or more appealing and not easily reproduced by competitors. Models that use large amounts of customer demand data should, in theory, yield goods and services customers prefer.

“Because AI models are largely derived from publicly-available data (meaning others can use the same data to build similar AI tools), moreover, monopoly control of such innovations is likely to be short-lived, absent protections leveraged to stifle competition (patents, mergers, partnerships).

Economic opportunities are likely to increase … [but] misinformation and other forms of epistemic corruption are also likely to increase across the board, so how we know what we know will be challenged. That will have downstream effects on large-scale human activity such as elections, crime and immigration, as well as on smaller-scale events such as family political arguments and even human flourishing. Ideally, the next 15 or so years is enough time for a modest improvement in how humans – individually and collectively – take in and process information to arrive at knowledge; at least enough of an improvement to ameliorate the impacts of epistemic corruption. But my guess is we’ll still be well short of this ideal by 2040.

“We will gain in some cases and lose in others, though ‘lose’ here is only from a price standpoint; innovations may yield net benefits for consumers. In either case, AI will transform business operations totally and dramatically, with effects comparable to the introduction of typewriting and adding machines or to the introduction of personal computers.

“In the socio-political space, what stands out to me is the potential for AI to, in Steve Bannon’s famous phrase, ‘flood the zone with shit.’ First, generative AI tools can generate enormous amounts of content (text, images, charts, etc.) with truly little effort. Second, generative AI tools are indifferent as to the truth-value of what they create. AI tools do not care if an image is realistic or not, whether an asserted fact is true, whether a hypothesis has evidence to support it or whether an opinion is plausible, at least not unless/until humans care.

“While many generative AI tools are likely to be used smartly in most cases, including by industry, NGOs [non-governmental organizations], political campaigns and others with louder voices in the socio-political space, rogue actors not constrained by boards of directors, voters, or other checks and balances have few incentives to do so. Most users will be inclined to ‘push the edge’ – use AI’s power to create and amplify misinformation just as much as it advantages them without creating undue risks of backlash. And our politics increasingly reward theatrics.

“All of this assumes we will be able to sort out important debates about permissions. I am less worried about permission to innovate – the U.S. is unlikely to adopt an extreme precautionary approach, in part because the EU is likely to land on an only modestly precautionary approach. Permissions to use the data on which models are trained, however (personal data and copyrighted material) will be trickier to manage and scale. Currently, rights to restrict the use of personal and/or copyrighted material are poorly enforced. That won’t last.

“AI will, well before 2040, have a ‘Napster’-like moment when models that assume unlimited and free access to the data that powers their tools are no longer sustainable models. Effective AI tools will need to find ways to secure appropriate permissions, methods that also scale well. My prediction is there will be some commercial opportunity here – private and/or public/private institutions will be created or should be created to allow developers to obtain permissions more efficiently from a massive set of data subjects and rights holders to use the large data sets that train foundation models.

“This may or may not be assisted by regulation, depending on the jurisdiction.

“Countries with highly functioning democracies (or that operate by executive fiat) may be able to pass regulations, but industry-initiated solutions will arise regardless of whether the government acts. Just as organizations such as BMI and ASCAP facilitated copyright permissions in the music industry, and as ‘global privacy control’ browser tools now exist to communicate privacy preferences, and as clearinghouse businesses (and, later, auctions) were created to sort out the market for radio spectrum licenses.

“Thus by 2040 the impact on humans is likely to be mixed. Economic opportunities are likely to increase, along with improved customer support, product selection, and e-commerce ease of use. Misinformation and other forms of epistemic corruption are also likely to increase across the board, so how we know what we know will be challenged. That will have downstream effects on large-scale human activity such as elections, crime and immigration, as well as on smaller-scale events such as family political arguments and even human flourishing.

“Ideally, the next 15 or so years is enough time for a modest improvement in how humans – individually and collectively – take in and process information to arrive at knowledge; at least enough of an improvement to ameliorate the impacts of epistemic corruption. But my guess is we’ll still be well short of this ideal by 2040.”

Daniel Schiff
The changes will likely be crosscutting and wide-ranging

Daniel Schiff, assistant professor of technology policy and co-director of the Governance and Responsible AI Lab at Purdue University, predicted, “By 2040, I expect that we will experience major changes in our daily lives, both visible and invisible, resulting from AI. These changes are likely to be crosscutting, affecting healthcare, education, labor, recreation, information consumption, socialization, human creativity and much more. A few strike me as especially significant:

• “Advances in healthcare owing to AI could be especially transformative, leading to extended lifespans, improved quality of life, better preventative care and public health, expanded access, and a reduction in the number of ailments that an average individual has to worry about. Adoption of administrative healthcare AI tools – such as those making electronic health records more-complete and interoperable, and those drawing on different sources of data such as synthetic data – could ease increases in healthcare costs somewhat.
• “A renaissance in education is necessary. Current and future generations of generative AI will likely lead to massive disruption in how teachers teach, students think, and educational institutions operate. Stakeholders in the education subsystem will need to carefully consider how to preserve critical thinking, adjust their pedagogy to counteract misconduct and apply AI education tools to foster upskilling rather than deskilling. Schools and learning are likely to look and feel very different, even if it takes a decade or more for these tools to become saturated, and even if classrooms and universities appear superficially structurally similar.
• “Robotics may become more affordable and pervasive, with increased presence of robots in healthcare, elderly care, education and other sectors. Long-standing questions about aspects of human-machine interaction and socialization will become increasingly salient as individuals interact with robots in their daily lives. Depending on the design of these systems, they may also substitute for human-human relationships, increasing isolation, alienation and other pathologies.
• “Disruption in labor and the economy is inevitable, if difficult to precisely predict. While key tasks and work processes will change, I expect the economy will continue to foster high-quality and low-quality jobs. Depending on how policy and industry actors approach skill adjustment, education, and the social safety net, work could involve enhanced surveillance and performance monitoring, or alternatively, shorter work weeks and higher productivity. While this direction is substantially up to how decision-makers help realize the efficiency gains of AI, it seems very likely that a large majority of occupations will involve more interaction with AI systems, both directly and on the back end. Significant engagement with AI systems will become a daily part of most workers’ lives.
• “Less change may occur at the level of political systems, barring incredibly rapid advancements in AI with equally robust political activity. A worst-case scenario, perhaps likely in some locations, is that some authoritarian countries will have come closer to perfecting dystopian forms of social control, such as through pervasive implementation of AI-enabled tracking, profiling and manipulation. With any luck, democracies will have advanced infrastructure and literacy enough to improve robustness against threats from AI-generated misinformation and social manipulation. However, changes resulting from social and economic upheaval, like labor disruption, educational gaps and/or the concentration of new wealth gains due to AI, could nevertheless lead to widespread dissatisfaction, new policy windows and shifting coalitions to advance goals like increased income distribution. Thus while major transformations of political systems (such as moving away from capitalism or abandoning authoritarianism or theocracy) is not likely, even moderate changes in political alignment and the broadening of acceptable policy solutions could induce dramatic changes in individuals’ lives.”

Larry Lannom
We’re in a world in which misinformation can feed off prior hallucinations

Larry Lannom, senior vice president at the U.S. Corporation for National Research Initiatives, predicted, “Advances in science and medicine will likely be accelerated through the use of AI, perhaps in ways that are currently unimaginable. There is a great deal to be hoped for in this, although also a great deal to fear. Manipulation at the genetic and cellular levels, for example, has the potential to greatly improve human life but also produce great harm, either through accident or malevolence.

Advances in the ability of AI-based processes to imitate humans are inevitable and are likely to have a negative impact on society. Trust is key to social coherence. … Keeping the impact of advanced AI-based technology more positive than negative will require explicit societal and governmental actions. The has already begun, but it will be important to consider not only the output of AI systems, but also the input to AI systems and input by AI systems themselves.

“Advances in the ability of AI-based processes to imitate humans are inevitable and are likely to have a negative impact on society. Trust is key to social coherence. Does that swell of approval for a given political candidate or corporate IPO reflect the input of a large number of people or of a single individual or AI system? While these sorts of manipulations are already possible today, they will become much easier with advanced technology.

“Keeping the impact of advanced AI-based technology more positive than negative will require explicit societal and governmental actions. The has already begun, but it will be important to consider not only the output of AI systems, but also the input to AI systems and input by AI systems themselves. It is certainly the case at this stage of development that the algorithms at the heart of AI systems primarily function by finding patterns in the input data, patterns that may or may not be discernable by humans due to the immense amount of data that is being processed.

“This is somewhat controlled in science, as the data comes curated through peer review and the need for theories to prove themselves via accurate predictions. This is not the case for the non-science world of information and therein lies the danger in AI systems consuming without distinction everything accessible on the Internet today. This is already obvious in current cases of bias in hiring. As the technology spreads and improves, the importance of selection of input data will grow. As the amount of information generated by AI systems increases it will lead to AI systems consuming input that has been previously generated by other AI systems, potentially resulting in ever-greater levels of authoritative-sounding misinformation that has simply doubled down on prior hallucinations.”

Keram Malicki-Sanchez
‘Tools should thoughtfully enrich, not overwhelm, the human spirit’

Keram Malicki-Sanchez, Canadian founder and director of VRTO Spatial Media World Conference and the Festival of International Virtual and Augmented Reality Stories, shared an excerpt from his essay “Virtual Layers, Human Stories: Autoethnography in Technological Frontiers.” He wrote:

“Alfred North Whitehead’s process philosophy (1929) proposes that existence comprises ephemeral experiential events rather than static objects. Though perceiving continuity, our world perpetually fluctuates. Whitehead’s conceptual abstractions provide a means of articulating the relational networks shaping reality. Donald Hoffman contends that consciousness constructs fitness-optimized perceptual ‘interfaces’ rather than accurately depicting reality (Hoffman, 2019). Our senses present not objective truth but biological utility crafted by natural selection. Hoffman proposes layered realities, with conscious agents occupying the surface above unconscious generative processes.

Just as virtual reality can make the ‘natural world’ come into sharper relief for its detail, generative AI can highlight what makes homo sapiens sapiens [modern humans] distinct. It is our invention, and thus it will carry our fingerprint. Ideally, it remains our companion, and the lessons we have learned from the mismanagement of social media come into much stronger consideration as wisdom we carry forward into this irrevocable new paradigm, so that we remain something for machines to dream about.

“Despite rapid progress, AI still struggles to capture the essence of human experience. Algorithms efficiently process data but cannot grasp life’s deeper meaning. AI falls short of representing the authenticity and the spirit animating human storytelling.

“As Hoffman suggests, our subjective perceptions may reflect evolutionary adaptations more than objective reality. Likewise, AI risks presenting distorted renderings downstream of human phenomenology. While ethical AI could aid autoethnographers, we must ensure technology does not undermine human dignity. Amidst change, vulnerable personal accounts remain vital, upholding our shared humanity. Tools should thoughtfully enrich, not overwhelm, the human spirit.

“Just as virtual reality can make the ‘natural world’ come into sharper relief for its detail, generative AI can highlight what makes homo sapiens sapiens [modern humans] distinct. It is our invention, and thus it will carry our fingerprint. Ideally, it remains our companion, and the lessons we have learned from the mismanagement of social media come into much stronger consideration as wisdom we carry forward into this irrevocable new paradigm, so that we remain something for machines to dream about.”

Nir Buras
Human-machine rules should achieve the reality we want for our children and grandchildren

Nir Buras, principal at the Classic Planning Institute, an urban design consultancy based in Washington, DC, wrote, “Intelligence cannot be artificial, so ‘artificial intelligence’ – isn’t. The idea of more-complex computational machinery begs two questions: Who is going to use it? And in what ways? The real questions cannot be boiled down to ‘AI, Problems and Solutions’ but instead should be framed as: How do we want to live our lives and work toward the best future for the lives of our children and grandchildren?

“This is an updated version of a set of rules I began writing several years ago in answer to Yuval Noah Harari’s ‘Homo Deus,’ which I found intellectually lacking. It is still a work in progress; a previous version was published by the U.S. Army Training and Doctrine Command as ‘Human-Machine Rules Version 05’ in May 2023.

The question is not whether humanity’s focus should shift to human interactions that leave more humans in touch with their destinies. It is at what cost do we avoid doing so now? We realize that today’s challenges cannot be addressed by applying the same methods of thinking that created them. Human-machine rules are therefore not about being ‘realistic’ today but about the reality we want for our children and grandchildren. We reject the idea that humanity should hand over the job of fixing the problems that the tech world generated to more technology and to those who created the problems in the first place.

“The question is not whether humanity’s focus should shift to human interactions that leave more humans in touch with their destinies. It is at what cost do we avoid doing so now? We realize that today’s challenges cannot be addressed by applying the same methods of thinking that created them. Human-machine rules are therefore not about being ‘realistic’ today but about the reality we want for our children and grandchildren. We reject the idea that humanity should hand over the job of fixing the problems that the tech world generated to more technology and to those who created the problems in the first place. These human-machine rules are based on and meant to support free, individual human choices. They can help define what degrees and controls are appropriate to ensure personal freedoms, secure personal property and minimize individual risk. They help indicate how consumer and government organizations might audit algorithms and manage equipment usage for societal and economic balances. They can help organize the dialogs around the various topics of human-machine interaction, especially in so called ‘ethical’ matters. Consequently, Human-Machine Rules are conceived to address any tool or machine, from the first flaked stone, to the ultimate ‘emotion machines.’ They can help standardize programming and user experience, and reason through the ethics of embedding technologies in people and their belongings.

“Human-machine rules are intended to be an outline for a legal code, similar to codes for motor vehicles, building and other construction and hazardous materials handling. The rules might be:

1. All human transactions and material transformations must be conducted by humans.
2. Humans may directly employ tools, machines and other devices in executing rule 1.
3. At all times, an individual human is responsible for the activity of any machine, technology, or program. All computing is visible to anyone at all times (no black box computing).
4. Responsibility for errors, omissions, negligence, mischief or criminal-like activity with regard to a technology is shared by every person in its organizational, operational and ownership chains, down to the last shareholder.
5. Any person can shut off any machine at any time. Penalties apply for inappropriately stopping machines.
6. Right to repair and easy recycling are required: a. All machines and parts greater than 1mm in size can be manually repaired with minimal tools. b. Components can be recycled using less than 5% of the energy required to produce them.
7. Personal data are personal property. Their use by a third party requires compensation.
8. A technology must mature to completeness prior to common use. a. Minimum viable products are unacceptable for common use. b. Consensus must emerge regarding a technology serving as an appropriate technology.
9. Parties replacing a technology with another shall ensure that, a. the technologies replaced are maintained in all their aspects, including but not limited to chain of materials, processes, and technologies supporting them; b. no less than 100 persons (masters) worldwide continue in perpetuity to use, develop, produce, practice and teach the said technology’s knowledge bases, areas of knowhow and skills. c. Replacement components are made available for 200 years for machines and 500 years for buildings, including stone, metals and wood for their repair. d. Children under age 12 are informed of the existence of previously-used technologies and exposed to them through museums, schooling and demonstrations.

“The proposed rules may be appended to the International Covenant on Economic, Social and Cultural Rights (ICESCR, 1976), part of the International Bill of Human Rights, which includes the Universal Declaration of Human Rights (UDHR) and the International Covenant on Civil and Political Rights (ICCPR). International Covenant on Economic, Social and Cultural Rights, www.refworld.org.; EISIL International Covenant on Economic, Social and Cultural Rights, www.eisil.org; UN Treaty Collection: International Covenant on Economic, Social and Cultural Rights, UN. 3 January 1976; Fact Sheet No.2 (Rev.1), The International Bill of Human Rights, UN OHCHR. June 1996; or any other appropriate legal platform.”

Sara ‘Meg’ Davis
Inequalities and human rights issues will be amplified

Sara (Meg) Davis, professor of digital Health and Rights at the University of Warwick, argued, “Health goals, for example, the promise of more rapid and accurate diagnosis and treatment, are often cited as an underlying rationale for the rapid growth of AI. But, in practice, without stronger AI governance the profound inequalities and human rights issues in global health risk being amplified. The foundations for future AI governance will be laid in the next year, at high speed. Health and human rights experts and advocates urgently need to be part of the conversation and to raise the three following concerns.

• “Whose security are we prioritizing? Real-world AI-related harms are disproportionately experienced by women and minority communities in high-income countries, as well as by many others in low- and middle-income countries who lack a voice in U.S. or UK tech governance. The familiar critiques apply to AI governance when it comes to reinforcing colonial inequalities: focusing narrowly on protecting wealthy countries from pandemics originating in the rest of the world; and ignoring equally critical and urgent needs of those dealing with weak health systems in the Global South, who are locked out of access to vaccines and more. In many countries with draconian cybersecurity laws, the digital securitization discourse has itself become a cause of insecurity for those targeted by police and authoritarian states. We need to demand digital security for all, not only for elites.
• “The spectre of self-certification by corporations for AI governance ought to ring loud alarm bells in global health. We have been here before, recently and embarrassingly: The State Party Self-assessment Reports countries dutifully completed for pandemic preparedness led the U.S. and UK to rank themselves highly, only to perform abysmally when they were tested in reality by COVID-19. Any self-certification process for AI safety must have independent review by experts, real social accountability mechanisms to enable communities to have a voice at every level of AI governance and whistle-blower mechanisms to enable anyone to raise the alarm when AI systems cause real-world harms.
• “Meaningful participation in AI governance. Given the rapid pace of AI development, Open AI rightly notes that laws and policies created now may not be fit for purpose a few years from now and may need repeated iterations. But how will this include robust and democratic community voice at every level? AI critic Timnit Gebru warns, “I am very concerned about the future of AI. Not because of the risk of rogue machines taking over. But because of the homogeneous, one-dimensional group of men who are currently involved in advancing the technology.” In global health, we have already experienced the lopsided influence of the private sector, private foundations, and interested donor states in multi-stakeholder platforms—and we will see this repeated in AI governance without pressure for truly democratic and inclusive governance, with a strong voice for communities and civil society to resist exploitative tokenism and promote meaningful participation in governance.

“In the Digital Health and Rights Project, an international consortium for which I am principal investigator, we are establishing one potential model of transnational participatory action research into digital governance that includes democratic youth and civil society participation from national to international levels. In the 1980s, AIDS activists around the world mobilized to demand a seat at the table in clinical trials and in global health governance mechanisms. That movement reshaped the global health landscape and saved millions of lives. Today we need to demand a voice in support of strong human rights and global health protections in AI governance.”

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