“The question of the future of humans and AI seems impossible to answer because of unexplainable humans, not because of unexplainable AI. So much depends on our use and control of AI. And that depends on who ‘our/we’ is. There are a number of issues here. Machines gave us huge gains in our ability to produce and eventually to transport things, including food. That in turn gave us too many choices, which often overwhelms us (see Barry Schwartz’s brilliant book ‘Paradox of Choice’).
“While poor people often lack the money/security to make good choices, rich people lack the time to enjoy/make use of all their options (as described in Eldar Shafir and Sendhil Mullainathan’s equally brilliant book ‘Scarcity’). We have gotten used to accelerated but overfilled time. Both then and now, you could lose your life in a few seconds, but in the past there were very few instant solutions for any problem.
Instead of regulating AI, we need to regulate its impact, and AI can actually be very helpful at that – both at predicting outcomes and at assessing counterfactuals. … Humans are needed to figure out what the goals of those AI tools and algorithms should be: How much to maximize sales versus reduce working hours? How much to maximize profits for the next year versus for the current CEO’s tenure versus on behalf of the investors who trade on the basis of a quarter’s earnings?
“We now live in a world of pills and instant shopping and even instant companions – found on dating apps (some real, some duplicitous) and also on many mental-health support apps. We expect immediate relief of our craving. But instead, our cravings never go away; rather, they turn into addictions.
“Indeed, what makes us most human may be how we perceive our own time and that of others. That was the fundamental gulf between the protagonist of the movie ‘Her’ (played by actor Joaquin Phoenix) and his AI ‘lover’ Samantha (Scarlett Johansson); she had more than a thousand lovers and time to pay attention to each of them. But in the end, what we’re seeking is share of mind from other humans, not fungible minutes of attention.
“Instead of regulating AI, we need to regulate its impact, and AI can actually be very helpful at that – both at predicting outcomes and at assessing counterfactuals. whether in healthcare, advertising or political campaigns. It can also automate huge amounts of physical labor and routine decision-making or repetitive work. However, it’s up to humans to figure out what the goals of those AI tools and algorithms should be: How much to maximize sales versus reduce/simplify working hours? How much to maximize profits for the next year, versus for the current CEO’s tenure, versus on behalf of the investors who trade on the basis of a quarter’s earnings? Things were very different when entrepreneurs built businesses for their grandchildren to inherit.
“Or is ‘we’ actually really people like Vladimir Putin and Donald Trump and Elon Musk – caught up in their own visions of a grandiose future (whether based on an imperial past or a future interstellar civilization)? They measure success differently, and they try to spread that vision whatever way they can. Mostly, they first seduce people with visions of power and money – and then make them complicit through the compromises required to realize those visions. Some make those compromises knowingly, but most are swept along, unexplainable even to themselves.
“AI will inevitably do a lot of useful things. I’d rather have an AI than a hungry, grumpy judge sit on my case in court. And, as a nondriver with no illusions about how safely I (and presumably most sensible people like me) drive, I’d rather sit in a car driven by a predictable AI that does not chat with the passengers, try to drink coffee, look at TikTok during stoplights or speed through yellow lights. Those points make sense and are only slightly controversial.
“To take a less abstract look, let’s use healthcare as an illuminating example. We can take healthcare as a model for pretty much everything, but with extremes. It’s a business, even though for some people – especially at the beginning of their careers – it’s also a calling. Indeed, it’s a very messy, complicated business. Its people – leaders and workers and customers – are overwhelmed with paperwork, with details, with conflicting regulations and requirements and stiff record-keeping protocols. And, of course, they must deal with privacy requirements that complicate the record-keeping and also serve to maintain silos for the incumbents. AI can help handle much of that. AI will take care of the paperwork, and it can make a lot of good, routine decisions – clearly and cleanly and with explanations. It’s very good at routine operations and at making decisions on the basis of statistics and evidence – as long as it’s prompted with the right goals and using the right data.
“Getting the right goals and using the right data are, of course, the big challenges. Is society really ready to consider the future consequences of its actions, not just a year from now, and not just a century from now, but in the foreseeable future? Think of the people today whose predictable diabetes we do not prevent this year and next; those people will eventually require expensive treatment and find their lives disrupted well before 2040. (See the recent frightening stats on diabetic amputations.)
“What about the kids who now spend their days in some sort of child storage because parents can’t afford or find childcare? They are likely to drop out of school, get into drugs and lose their way, and scramble as adults to make money however they can in 2040 and beyond. Then there are the mothers today who get inadequate pre- and post-natal care and counseling. They may suffer a miscarriage or fail to provide a nurturing childhood, with all the inevitable consequences by 2040.
“We need AI to predict the positive counterfactuals of changing our approach to fostering and investing in health in advance, versus spending too late on remedial care. If we use the right data and make the right decisions, for each patient specifically, AI will allow us to do one broad, important thing right: It will reduce busywork and free those who joined healthcare as a calling to be better humans – paying human attention to each of the individuals they serve.
“Our challenge – in healthcare as elsewhere – is to train humans to be human. Training AIs is scalable: Train one and you can replicate it easily. But humans must be trained one by one. Yes, they learn well in groups, but only if they are recognized as individuals by other individuals.
In the positive parts of the planet, AI – in its ethical form – will win out and we’ll start focusing not so much on what AI can do, but on what we ask it to do. Do predatory business models reign supreme, or do we focus more on the long-term welfare of our people and our society? In short, we need explainability of the goals and the outcomes more than we need an understanding of the technological underpinnings. … We need to understand our own motivations and vulnerabilities. We need to understand the long-term consequences of everyone’s behavior.
“There are mostly positive and mostly negative scenarios for the near future. Both will happen across different societies and, of course, they will interact and intersect. There will be stark differences across countries and across boundaries of class and culture within countries. I doubt that one side or the other will win out entirely, but we can collaborate to help spread the good scenarios as widely as possible. We’ll still be asking the same question in 2040: ‘How will it turn out?’ It won’t be over.
“As a society, we need to use the time we spend on rote decision-making and rule-following – which AIs can do well – to free ourselves and train ourselves to be better humans. We need to ask questions and understand the answers. We need to be aware of others’ motivations – especially those of the AI-powered, business-model-driven businesses (and their employees) that we interact with every day.
“In the positive parts of the planet, AI – in its ethical form – will win out and we’ll start focusing not so much on what AI can do, but on what we ask it to do. Do predatory business models reign supreme, or do we focus more on the long-term welfare of our people and our society? In short, we need explainability of the goals and the outcomes more than we need an understanding of the technological underpinnings.
“And we need to understand our own motivations and vulnerabilities. We need to understand the long-term consequences of everyone’s behavior. We need the sense of agency and security that you get not from doing everything right, but from learning by making, acknowledging and fixing mistakes. We need to undergo stress and get stronger through recovery. What makes us special in some ways is our imperfections: the mistakes we make, the things we strive for and the things we learn.”
This essay was written in November 2023 in reply to the question: Considering likely changes due to the proliferation of AI in individuals’ lives and in social, economic and political systems, how will life have changed by 2040? This and more than 150 additional responses are included in the report “The Impact of Artificial Intelligence by 2040”