Our AI Odyssey
By Joseph S. Nye - November 26, 2021
CAMBRIDGE
– An elder statesman, a retired Big Tech CEO, and a computer scientist
meet in a bar. What do they talk about? Artificial intelligence, of
course, because everyone is talking about it – or to it, whether they
call it Alexa, Siri, or something else. We need not wait for a
science-fiction future; the age of AI is already upon us.
Machine-learning, in particular, is having a powerful effect on our
lives, and it will strongly affect our future, too.
That is the
message of this fascinating new book by former US Secretary of State
Henry A. Kissinger, former Google CEO Eric Schmidt, and MIT dean Daniel
Huttenlocher. And it comes with a warning: AI will challenge the primacy
of human reason that has existed since the dawn of the Enlightenment.
Can
machines really think? Are they intelligent? And what do those terms
mean? In 1950, the renowned British mathematician Alan Turing suggested
that we avoid such deep philosophical conundrums by judging performance:
If we cannot distinguish a machine’s performance from a human’s, we
should label it “intelligent.” Most early computer programs produced
rigid and static solutions that failed this “Turing test,” and the field
of AI went on to languish throughout the 1980s.
But a
breakthrough occurred in the 1990s with a new approach that allowed
machines to learn on their own, instead of being guided solely by codes
derived from human-distilled insights. Unlike classical algorithms,
which consist of steps for producing precise results, machine-learning
algorithms consist of steps for improving upon imprecise results. The
modern field of machine-learning – of programs that learn through
experience – was born.
The technique of layering machine-learning
algorithms within neural networks (inspired by the structure of the
human brain) was initially limited by a lack of computing power. But
that has changed in recent years. In 2017, AlphaZero, an AI program
developed by Google’s DeepMind, defeated Stockfish, the most powerful
chess program in the world. What was remarkable was not that a computer
program prevailed over another computer program, but that it taught
itself to do so. Its creators supplied it with the rules of chess and
instructed it to develop a winning strategy. After just four hours of
learning by playing against itself, it emerged as the world’s chess
champion, beating Stockfish 28 times without losing a match (there were
72 draws).
AlphaZero’s play is informed by its ability to
recognize patterns across vast sets of possibilities that human minds
cannot perceive, process, or employ. Similar machine-learning methods
have since taken AI beyond beating human chess experts to discovering
entirely new chess strategies. As the authors point out, this takes AI
beyond the Turing test of performance indistinguishable from human
intelligence to include performance that exceeds that of humans.
ALGORITHMIC POLITICS
Generative
neural networks also can create new images or texts. The authors cite
OpenAI’s GPT-3 as one of the most noteworthy generative AIs today. In
2019, the company developed a language model that trains itself by
consuming freely available texts from the internet. Given a few words,
it can extrapolate new sentences and paragraphs by detecting patterns in
sequential elements. It is able to compose new and original texts that
meet Turing’s test of displaying intelligent behavior indistinguishable
from that of a human being.
I know this from experience. After I
inserted a few words, it scoured the internet and in less than a minute
produced a plausible false news story about me. I knew it was spurious,
but I do not matter that much. Suppose the story had been about a
political leader during a major election? What happens to democracy when
the average internet user can unleash generative AI bots to flood our
political discourse in the final days before people cast their ballots?
Democracy
is already suffering from political polarization, a problem exacerbated
by social media algorithms that solicit “clicks” (and advertising) by
serving users ever-more extreme (“engaging”) views. False news is not a
new problem, but its fast, cheap, and widespread amplification by AI
algorithms most certainly is. There may be a right to free speech, but
there is not a right to free amplification.
These fundamental
issues, the authors argue, are coming to the fore as global network
platforms such as Google, Twitter, and Facebook employ AI to aggregate
and filter more information than their users ever could. But this
filtration leads to segregation of users, creating social echo chambers
that foment discord among groups. What one person assumes to be an
accurate reflection of reality becomes quite different from the reality
that other people or groups see, thus reinforcing and deepening
polarization. AI is increasingly deciding what is important and what is
true, and the results are not encouraging for the health of democracy.
CRACKING NEW CODES
Of
course, AI also has huge potential benefits for humanity. AI algorithms
can read the results of a mammogram with greater reliability than human
technicians can. (This raises an interesting problem for doctors who
decide to override the machine’s recommendation: will they be sued for
malpractice?)
The authors cite the case of halicin, a new
antibiotic that was discovered in 2020 when MIT researchers tasked an AI
with modeling millions of compounds in days – a computation far
exceeding human capacity – to explore previously undiscovered and
unexplained methods of killing bacteria. The researchers noted that
without AI, halicin would have been prohibitively expensive or
impossible to discover through traditional experimentation. As the
authors say, the promise of AI is profound: translating languages,
detecting diseases, and modeling climate change are just a few examples
of what the technology could do.
The authors do not spend much
time on the bogeyman of AGI – artificial general intelligence – or
software that is capable of any intellectual task, including relating
tasks and concepts across disciplines. Whatever the long-term future of
AGI, we already have enough problems coping with our existing generative
machine-learning AI. It can draw conclusions, offer predictions, and
make decisions, but it does not have self-awareness or the ability to
reflect on its role in the world. It does not have intention,
motivation, morality, or emotion. In other words, it is not the
equivalent of a human being.
But despite the limits of existing
AI, we should not underestimate the profound effects it is having on our
world. In the authors’ words:
“Not recognizing the many modern
conveniences already provided by AI, slowly, almost passively, we have
come to rely on the technology without registering either the fact of
our dependence or the implications of it. In daily life, AI is our
partner, helping us to make decisions about what to eat, what to wear,
what to believe, where to go, and how to get there…But these and other
possibilities are being purchased – largely without fanfare – by
altering the human relationship with reason and reality.”
THE AI RACE
AI
is already influencing world politics. Because AI is a general enabling
technology, its uneven distribution is bound to affect the global
balance of power. At this stage, while machine-learning is global, the
United States and China are the leading AI powers. Of the seven top
global companies in the field, three are American and four are Chinese.
Chinese
President Xi Jinping has proclaimed the goal of making China the
leading country in AI by the year 2030. Kai-Fu Lee of Sinovation
Ventures in Beijing notes that with its immense population, the world’s
largest internet, vast data resources, and low concern for privacy,
China is well placed to develop its AI. Moreover, Lee argues that having
access to an enormous market and many engineers may prove more
important than having world-leading universities and scientists.
But
the quality of data matters as much as the quantity, as does the
quality of chips and algorithms. Here, the US may be ahead. Kissinger,
Schmidt, and Huttenlocher argue that with data and computing
requirements limiting the development of more advanced AI, devising
training methods that use less data and less computer power is a
critical frontier.
ARMS AND AI
In addition to the economic
competition, AI will have a major impact on military competition and
warfare. In the authors’ words, “the introduction of nonhuman logic to
military systems will transform strategy.” When AI systems with
generative machine-learning are deployed against each other, it may
become difficult for humans to anticipate the results of their
interaction. This will place premiums on speed, breadth of effects, and
endurance.
AI thus will make conflicts more intense and
unpredictable. The attack surface of digital networked societies will be
too vast for human operators to defend manually. Lethal autonomous
weapons systems that select and engage targets will reduce the
capability of timely human intervention. While we may strive to have a
human “in the loop” or “on the loop,” the incentives for preemption and
premature escalation will be strong. Crisis management will become more
difficult.
These risks ought to encourage governments to develop
consultations and arms-control agreements; but it is not yet clear what
arms control for AI would look like. Unlike nuclear and conventional
weapons – which are large, visible, clunky, and countable – swarms of
AI-enabled drones or torpedoes are harder to verify, and the algorithms
that guide them are even more elusive.
It will be difficult to
constrain the development of AI capabilities generally, given the
importance and ubiquity of the technology for civilian use. Nonetheless,
it may still be possible to do something about military targeting
capabilities. The US already distinguishes between AI-enabled weapons
and autonomous AI weapons. The first are more precise and lethal but
still under human control; the latter can make lethal decisions without
human operators. The US says it will not possess the second type.
Moreover,
the United Nations has been studying the issue of a new international
treaty to ban such weapons. But will all countries agree? How will
compliance be verified? Given the learning capability of generative AI,
will weapons evolve in ways that evade restraints? In any event, efforts
to moderate the drive toward automaticity will be important. And, of
course, automaticity should not be allowed anywhere near nuclear-weapons
systems.
THE LEADERSHIP LAG
For all the lucidity and wisdom
in this well-written book, I wish the authors had taken us further in
suggesting solutions to the problems of how humans can control AI both
at home and abroad. They point out that AI is brittle because it lacks
self-awareness. It is not sentient and does not know what it doesn’t
know. For all its brilliance in surpassing humans in some endeavors, it
cannot identify and avoid blunders that would be obvious to any child.
The Nobel laureate novelist Kazuo Ishiguro dramatizes this brilliantly
in his novel Klara and the Sun.
Kissinger, Schmidt, and
Huttenlocher note that AI’s inability to check otherwise clear errors on
its own underscores the importance of developing testing that allows
humans to identify limits, review proposed courses of action, and build
resilience into systems in case of AI failure. Societies should permit
AI to be employed in systems only after its creators demonstrate its
reliability through testing processes. “Developing professional
certification, compliance monitoring, and oversight programs for AI –
and the auditing expertise their execution will require – will be a
crucial societal project,” the authors write.
The authors
conclude with a proposal for a national commission comprising respected
figures from the highest levels of government, business, and academia.
It would have the dual function of ensuring that the country remains
intellectually and strategically competitive in AI, while also raising
global awareness of the technology’s cultural implications. Wise words,
but I wish they had told us more about how to achieve these important
objectives. In the meantime, they have produced a wonderfully readable
introduction to issues that will be critical to humanity’s future and
will force us to reconsider the nature of humanity itself.