|
A peer-reviewed
electronic journal published by the Institute for Ethics and ISSN
1541-0099 17(1)
– January 2008 |
The Technology of Mind and a New Social Contract
Bill Hibbard
Journal of Evolution and Technology -
Vol. 17 Issue 1 – January 2008 - pgs 13-22
http://jetpress.org/v17/hibbard.html
Abstract
The progress of biology, neuroscience and
computer science makes it clear that some time during the twenty-
first century we will master the technologies of mind and life. We will build machines more
intelligent than ourselves, and modify our own brains and bodies to increase
our intelligence, live indefinitely and make other changes. We live together
according to a social contract,
consisting of laws, morals and conventions governing our interactions. This
social contract is based on assumptions we rarely question: that all humans
have roughly the same intelligence, that we have limited life spans and that we
share a set of motives as part of our human
nature. The technologies of mind and life will invalidate these assumptions
and inevitably change our social contract in fundamental ways. We need to
prepare for these new technologies so that they change the world in ways we
want rather than just stumbling into a world that we don't.
The Technology of Mind
Neuroscience
is discovering many correlations between the behaviors of physical brains and
minds. If brains do not explain minds then these correlations would be
coincidences, which is absurd. Furthermore, relentless improvements in computer
technology make it clear that we will build machines that match the ability of
brains to generate minds like ours, sometime during the twenty-
first century. This technology of mind will enable us to build
machines much more intelligent than ourselves, and to increase the intelligence
of our human brains.
We
do not yet understand how brains generate our intelligent minds, but we know
some things about how brains work. Minds are fundamentally about learning. Baum
makes a convincing case that brains do what is called reinforcement learning (Baum 2004). This means that brains have a
set of values (sometimes called rewards), such as food is good, pain is bad,
and successful offspring are good, and learn behaviors that increase the good
values and decrease the bad values. That is how genetic evolution works, with
the value that creating many copies of genes is good. A mutation to a gene
creates a new gene that is expressed in organisms that carry the mutation. If
those organisms survive and reproduce more successfully than others of their
species, many copies of the mutated gene are created. But genetic evolution
learns by pure trial and error. Human and animal brains are more efficient. If
you have a new idea, you try it out to see if it works. If it doesn't, you have
a model of the world (that is, you can reason) that you use to trace cause and
effect to estimate the cause of the failure.
Brains
understood as reinforcement learners consist of:
1. Reinforcement values to be increased or
decreased - these are the basic motives of behavior.
2. Algorithms for learning behaviors based
on reinforcement values.
3. A
simulation model of the world, itself learned from interactions with the world
(the reinforcement value for learning the simulation model is accuracy of
prediction).
4. A
discount rate for balancing future versus current rewards (people who focus on
current rewards and ignore the future are generally judged as not very
intelligent).
This
decomposition of mental functions gives us a way to understand the options
available to us in the design of intelligent machines. While we do not yet know
how to design learning algorithms and simulation models adequate for creating
intelligence, we can reasonably discuss the choices for the values that
motivate their behaviors and the discount rate for future rewards.
In
spite of our overall ignorance of how intelligence works, well-known
reinforcement learning algorithms have been identified in the neural behaviors
of mammal brains (Brown, Bullock and Grossberg 1999; Seymour et al. 2004). And
reinforcement learning has been used as the basis for defining and measuring
intelligence in an abstract mathematical setting (Legg and Hutter 2006).
The
most familiar measure of intelligence is IQ, but it is difficult to understand
what a machine IQ of a million or a billion would mean. As is often
pointed out, intelligence cannot be measured by a single number. But one
measure of a mind’s intelligence, relevant to power in the human world, is the
number of humans the mind is capable of knowing well. This will become
a A practical measure of intelligence,
as we develop machines much more intelligent than humans.,
is the number of people that a mind can know well. Humans evolved
an ability to know about 200 other people well, driven by the selective
advantage of working in groups (Bownds 1999). Now Google is working hard to
develop intelligence in its their enormous
servers, which already keep records of the search histories of hundreds of
millions of users. As theseir
servers develop the ability to converse in human languages, these
search histories will evolve into detailed simulation models of our minds.
Ultimately, large servers will know billions of people well. This will give
them enormous power to predict and influence economics and politics; rather
than relying on population statistics, such a mind will know the political and
economic behavior of almost everyone in detail. As is often
pointed out, intelligence cannot be measured by a single number. But one
measure of a mind’s intelligence, relevant to power in the human world, is the
number of humans the mind is capable of knowing well.
There
are already experiments with direct electronic interfaces to brain nerve cells.
This will ultimately evolve into prosthetic enhancements of human brains and uploading human minds (Kurzweil 1999;
Moravec 1999), in which humans minds will migrate out of human brains and into
artificial brains. The technologies of mind and life will blur the distinction
between humans and machines.
The Social Contract
Teamwork
helps individuals succeed at survival and reproduction, and this has created
evolutionary pressure for teamwork in humans and other animals. Thus we have
social abilities such as language, and social values such as liking, anger,
gratitude, sympathy, guilt and shame, that enable us to work in teams.
A
fascinating experiment called the Wason selection test demonstrates that the
ability of human subjects to solve a type of logic puzzle depends on whether or not it
is worded in terms of social obligation: most subjects can solve it when it
relates to social obligation and cannot solve it otherwise (Barkow, Cosmides
and Tooby 1992). This indicates that humans have mental processes dedicated to
satisfying the values necessary for cooperation, including especially
evaluating whether the subject is being cheated.
Social
values and the special processes dedicated to the logic of social obligation,
which evolved in human brains because cooperation benefits individuals, are at
the roots of ethics. Specifically, ethics are based in human nature rather than
being absolute (but note that human nature evolved in a universe governed by
the laws of mathematics and physics, and hence may ultimately
reflect an absolute). Thomas Hobbes defined a theoretical basis for this view
in his description of the social contract that humans enter into in order to
bring cooperation to their competition (Hobbes 1651).
The
social contract as described by Hobbes gave different rights and obligations to
rulers and subjects. That has evolved in modern societies into a contract in
which everyone has the same rights and obligations, but certain offices that
individuals may (temporarily) occupy have "special" rights and
obligations. The legal systems in most countries are based on the equality of
individuals, although there is a spectrum between equality of opportunity and equality
of results. Of course, there is also inequality based on country and family
of birth, and plenty of corruption that undermines equality. But, over the long
haul of human history, despite reversals in some societies and during some
periods, there is gradual progress toward the ideal of equality. In many
countries,
progress includes elimination of slavery and real monarchies, popular election
of leaders, and collective support for educating the young and caring for the
elderly.
Changing Assumptions
The
social contract grows out of our human nature and is based on rarely-questioned
assumptions, including:
1. Humans
all have roughly the same intelligence (if you doubt this, consider that the
chess skill that distinguishes Garry Kasparov from most other humans has been
matched by computers, but the language and movement skills he shares with other
humans are far beyond current computers). We assume this when we say that our
competitive economic system provides equal opportunity.
2. Humans
are motivated by the roughly the same set of values, as part of our shared
human nature. Tax codes and other laws make many assumptions about human
motives.
3. Humans
have limited and roughly equal life spans. We assume this when we support
indefinite retirement benefits past a certain age, and when we expect
inheritance taxes to prevent indefinite growth of family wealth.
The
technologies of mind and life will invalidate these assumptions, with profound
consequences for our social contract. For example, a less intelligent person
will be unable to converse meaningfully with a person of radically greater
intelligence. This is similar to the way a young child cannot converse at an
adult level, except that the gap will be much larger. The most intelligent
minds may know billions of ordinary humans well, and understand large-scale
social interactions in a "single thought." A conversation between two
super-intelligent minds about such matters will be meaningless to an ordinary
human. This will severely limit the ability of less intelligent humans to
participate in economic and political discussions. If the super-intelligent
minds are motivated by values similar to those of current humans, they will
exclude less intelligent humans from important political and economic
decisions, just as adults exclude children now.
Even
in current democratic societies with roughly uniform intelligence, some people
amass wealth nearly a million times as great as that of average people. If that
wealth enables those people to buy commensurately more intelligent brains in
the service of their self-interest, and if those people live indefinitely, they
will eventually amass enough wealth and power to essentially own and rule the
world.
There
are numerous differences in legal rights and responsibilities based on
intelligence and mental development, including:
1. The
US Supreme Court has held that executing mentally retarded
people violated the Eighth Amendment's prohibition of cruel and unusual
punishments (Atkins v. Virginia
2002).
2. In
many jurisdictions, a person is insane and not legally
responsible if, because of mental defect, they do not understand that their
actions are wrong (Goldstein 1967).
3. During
the first half of the twentieth century, compulsory sterilization of mentally
retarded people occurred in the US and other countries (Kevles 1985).
4. In
many countries, children have a separate legal system.
5. Animals
have a very different legal status from humans.
In
a society with an enormous range of intelligence, the less intelligent members
will not be able to understand the language and moral concepts of the most
intelligent. Given the precedents in our current legal system, this will
certainly lead to different legal rights and responsibilities for people with
different intelligence.
Humans
have complex sets of motivations that combine self-interest with compassion for
others. But organizations may create super-intelligent minds with simple
motives to promote the organizations' interests. Corporations may create minds
whose sole value is to increase corporate profits, and governments may create
minds whose sole value is to increase political or military power. We already
see this issue when corporations behave in ways that would horrify stockholders
if they encountered such behavior in their own lives, rather than in distant
communities largely invisible to stockholders (Gedicks 2001). One example is the For
example, operations by multi-national
mining corporations that degrade the environment near mines and cause the
deaths by poisoning of indigenous people. Similar detachment may exist between
future human owners and their super-intelligent agents. If these agents play a
human-like role in the social contract, but without any of the compassion of
human nature, they may be responsible for great harm to humans. Of course,
humans often behave with little compassion, and the social contract includes
sanctions against such behavior. But our social contract never contemplated the
combination of super-intelligence and absolute lack of compassion.
A New Social Contract
The
first attempt to modify the social contract for the technology of mind was
Asimov's Laws of Robotics, which defined constraints on the behavior of robots
(Asimov 1942). But such constraints are inevitably ambiguous, and as Ray
Kurzweil has
pointed out "there is no purely technical strategy that is workable
in this area, because greater intelligence will always find a way to circumvent
measures that are the product of a lesser intelligence" (Kurzweil 2005).
However,
the technology of mind will give us freedom to choose the motives of machine
and enhanced human minds, and we can design them to not
to want
to circumvent measures to protect others. We can design them to value the
well-being of other humans. We could try to design a complex formula for
measuring human well-being, but the measure that best values human freedom is
to allow each person to express their own well-being in their happiness (Pearce
1998; Hibbard 2002), or to be more precise, their expressions of long-term life
satisfaction rather than short-term euphoria (Ryan and Deci 2001). This fits
naturally in the form of a proposed new social contract: in exchange for
significantly greater than normal human intelligence, a mind must value the
long-term life satisfaction of all other intelligent minds.
Of
course, there are many details in how this happiness is defined and how the
happiness values of many minds are combined into a single reinforcement value
for the super-intelligent mind. For example, the discount rate for future
rewards should strongly emphasize the long term to avoid reinforcing behaviors
that pander to short-term pleasure at the expense of long-term unhappiness.
Valuing
human happiness requires recognizing humans and their emotions.
Super-intelligent minds will need to learn to classify humans and other minds,
and their emotions, according to the general consensus of the way humans
classify. Because humans and other minds will evolve under the technologies of
mind and life, super-intelligent minds will need to continually relearn their
classifications, reinforced by agreement with the general human consensus.
In
order to promote equality, unhappiness should be weighted more heavily than
happiness so efforts are focused on helping unhappy minds rather than those who
are already happy. We see such behavior among parents who focus their energy on
the children who need it most, and in modern societies that provide special
services to people in need. This principle will avoid the tyranny of the majority, in which a majority of people want the
oppression of a minority.
Super-intelligent
minds will need values for predictive accuracy to reinforce learning of
simulation models and may seek to improve their predictive accuracy by taking
needed resources away from others. In order to avoid this, super-intelligent minds
should only increase their computing
resources
only when their simulation models say that the resulting increase in
predictive accuracy will produce a net increase in the happiness of others.
Humans
who are inconsolably unhappy due to physical or mental illness, pose a complex
set of issues for reinforcement values. Values for happiness might motivate
super-intelligent minds to cause the deaths of such people. This could be
avoided by accounting for dead people at a maximally unhappy value, so that super-intelligent
minds always see death as an event to avoid.
These
details of engineering super-intelligent minds to protect human values will be
tricky, leading some to suggest avoiding the technologies of life and mind. For
example, Fukuyama warns against changes to human nature and considers the
entire transhumanist program to be dangerous (Fukuyama, 2002). Like most
significant ideas, transhumanism is dangerous, but it is not
politically feasible to stop the progress of technology. The human drives for improved
health, longer lives, reduced labor, and improved minds and bodies are too
strong to deny. The technologies of mind and life are inevitable and will
change human nature. Our best course is a new social contract to regulate these
changes, rather than a futile effort to try to stop them or simply allowing
each individual to make whatever changes they like.
Benefits of New
Technologies
The
technologies of mind and life are really extensions of the ways that most
people are already trying to improve their lives. We exercise, regulate our
diets, and spend enormous sums on medical care, to improve our health and live
longer. We read, study, solve puzzles and play games in order to improve our
minds. We look for easier ways to accomplish our tasks, and save for
retirement, in order to reduce our labor.
With
the right social contract, the new technologies will free us from the need to
commute to jobs where we spend most of our days. Instead we will spend our time
with family and friends, and in the company of new minds that tell funnier
jokes, produce better music and movies, cook better food, know more science,
help us find our own creativity, and love us better than any ordinary human
can. The new technologies will enable us to live in perpetual good health,
satisfying our curiosity about everything in the world, developing deep loving
relations with others, and travelling to the reaches of the universe. Our
greatly expanded mental abilities will enable us to know more people and to
have a much deeper understanding of the world. Assuming upgraded humans will
value accuracy of prediction, they will still be curious about the world. Under
the proposed new social contract, the xenophobia that causes so much misery
will be absent in artificial minds and upgraded humans, and in order to promote
general happiness they will counsel the remaining natural humans to resist their
own xenophobic urges.
Once
people realize that all these things are possible, for themselves or for their
children, they will know that they must let nothing prevent this future. On a
personal level, this realization is a motive for people to preserve their
health until the new technologies arrive. On a social level, it is a motive to
create a new social contract that will enable everyone to benefit from them.
The benefits are clearly worth the risks that Fukuyama and others have
described.
Politics
Any
change to the social contract to regulate the technology of mind will have to
be worked out in a political process. The good news is that the most
technically advanced countries, where the technology will be developed, are
democracies. Democracy works best for issues on which the public is informed
and interested. A challenge for transhumanists is to educate the public and to
help create a movement for promoting and regulating the technology of mind,
similar to the political movements for protecting the environment and consumer
safety, and for controlling weapons of mass destruction.
The
technologies of mind and life promise great benefits, so we must avoid the
temptation to ban them altogether (which is undoubtedly technically and
politically impossible in the long run). We must also avoid provoking a
libertarian backlash against a ban that would give everyone
total freedom to experiment with these technologies. We would not consider
granting such freedom to experiment with nuclear, chemical and biological
weapons, and the technologies of mind and life are ultimately much more
dangerous than such weapons. We should seek the middle path of regulated
development, between a ban and total freedom (Hughes 2004).
Social Security:
The debate over the US Social Security system (and similar debates in other
countries) is based on 75-year economic projections, and thus brings the issues
of the technologies of mind and life into current politics. The Social Security
Trustees estimate that the annual rate of growth in US productivity, which has
averaged 2.9% over the past 10 years (Bureau of Labor Statistics 2006), will
decrease to 1.7% by 2013 and then remain at that level until 2080 (Social
Security Administration 2006). Under this estimate, the
Social Security Trust Fund will be depleted by 2042 (increasing the estimate of
productivity growth delays the date at which the Trust Fund is depleted,
possibly forever). One suggested solution to the problem of Trust Fund
depletion is to gradually raise the retirement age.
However,
during the next 75 years, intelligent machines are likely to gradually
out-compete humans for all jobs (Moravec 1999). In order to meet people’s needs
as unemployment approaches 100 per cent%,
Moravec suggests gradually reducing the retirement age down to birth in the US
Social Security system and other national pension plans. By enabling more goods
and services to be produced by fewer human workers, these machines will
increase productivity until it is essentially infinite. (For a detailed
discussion of the economic effects of intelligent machines, see Marshall
Brain's Robotic Nation essays (Brain 2003)). There is a clear conflict between
the future envisioned by the Social Security Trustees, in which productivity
growth declines and the retirement age increases, and the future envisioned by
Moravec and other Artificial Intelligence (AI) researchers, in which
productivity growth increases and the retirement age decreases.
Social
Security privatization is a proposal to end the current practice of using the
contributions of one person to subsidize the benefits of others, and instead to
isolate each person's contributions and benefits in a private account. This is
exactly the opposite of what will be needed as intelligent machines create
great wealth but displace the population from the work force. There must be a
mechanism for sharing that wealth, on an international scale.
Intelligent Weapons:
The Future Combat Systems project, to automate and network the battlefield,
estimated to cost $127 billion, is the largest in US military history. The
Department of Defense is the largest funding source for AI research. Other
countries have similar, although smaller, projects. These raise immediate
ethical questions about machines making life-and-death decisions in battle
(Johnson 2005). Longer term, intelligent weapons will enable a small group to
rule without the need for the cooperation of citizen soldiers. These issues
should force a public debate.
The
public movement to regulate intelligent machines can point to treaties banning
chemical and biological weapons as precedents for banning intelligent weapons.
Weapons more intelligent than humans should be seen as analogous to these
threats, and the movement to control such intelligent weapons should learn from
the successes and failures of those earlier efforts.
Protecting Children:
A great deal of politics is motivated by people’s desire to protect their
children, reflected in what are often called "values issues." It is
natural that many people are frightened of the technologies of mind and life,
and worry about the nightmare world their children may inherit. We need to be
sensitive to these concerns and avoid expressing careless attitudes toward the
fate of humanity or of those who are not on the cutting edge of technology.
In
fact, most people understand that the advance of technology cannot be stopped
and are unlikely to be drawn into a serious movement to ban the technologies of
mind and life. By acknowledging people's concerns for their children's futures,
we can lead those concerns into a progressive movement to develop such
technologies in ways that promise a better life to all humans through a new
social contract.
Conclusions
The
technologies of mind and life are coming and will bring enormous benefits. They
will also change assumptions that underlie the social contract that governs
interactions among humans, with potentially undesirable consequences. Some
advocate banning these technologies but, given the promised benefits, this is
politically impossible. Instead, we should support regulated development to
ensure that all humans benefit from these technologies, rather than a small
group benefiting at the expense of most other humans. In particular, minds
should only be permitted to have
significantly greater than natural human intelligence only if
they value the long-term life satisfaction of all other intelligent minds.
Achieving
the goal of regulated development will require a popular political movement.
This will depend on educating the public about these technologies, and about
their potential dangers and promised benefits to future generations.
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