IEEE Technology and Society Magazine - March 2020 - 17

Along the way, this deployment
in society has forced the realization that these algorithms have social impacts that could be positive
or negative. For example, we have
realized that biases hidden in data
and algorithms could lead to more
discrimination, in the simplest case
simply because of the data imbalance: facial recognition algorithms
have been found to underperform
on gender and racial minorities [5].
Furthermore, above and beyond
hidden biases, given the high impact potential of ML research, the
question stands of whether practitioners are acting with the best interests of humanity and society in
mind when developing their tools
and applications.
As ML researchers and engineers,
we believe that we have a shared responsibility to consider both ethics
and moral values when we choose
what we work on, for what organization, and whether the products we
contribute to directly or indirectly will
be beneficial to humanity or more
likely to end up hurting more than
helping. Unfortunately, very few of
us have been trained to think about
these questions. Instead, most of us
have focused from a very young age
on mathematics and computer science and not so much on philosophy
and other humanities. A good step
towards learning about these issues
is to consult the documents proposing ethical guidelines for AI, which
we will cover in the next section of
this article. Furthermore, in order to
offer a guiding direction for such debates and soul-searching within the
scope of ML, we propose the following self-directed questions:

4) How does my job fit with my
values?
We are conscious that the questions listed above are subjective
and the answers will depend highly
on the values and ethics of the individual answering them. Nonetheless,
we hope that work on some applications, such as the design and deployment of lethal autonomous weapons
and automatic surveillance, will
clearly be seen to contradict fundamental rights and dignity, as defined
in, among other places, the UN Declaration of Human Rights [41]. Other
applications of ML, such as those increasing the efficiency of advertising
or beating the stock market, are less
clear cut in their moral value, and
merit informed debate and discussion within the scientific community
and society at large. As some of us
become more conscious of the potential or definite social impact of
ML, we have the opportunity, if not
the duty, to make our voices heard.
A good example of this is a recent
letter, signed by numerous scientists, calling for an international treaty to ban lethal autonomous weapon
systems, e.g., killer drones. Killer
drones can decide to shoot at a person - without the human involvement that would make it possible
to take the broad social, moral, and
psychological context into account
and potentially decide to abort the
mission (for instance, when the target is in a school or at a family dinner
surrounded by women and children).
Finally, while the legal frameworks to oversee and limit research
and development violating these
principles are often and unfortunately updated in a reactive rather
than a proactive manner, we believe
that we should not wait until all of
the dots between ML and ethics
are formally connected by legislation and regulation. We believe that
we have a responsibility to educate

1) How is the technology that I am
working on going to be used?
2) W ho w i l l benef it or su f fer
from it?
3) How much a nd what socia l
impact will it have?
MARCH 2020

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IEEE TECHNOLOGY AND SOCIETY MAGAZINE

ourselves, to think ahead about potential consequences, to use our
internal moral compasses, and to
consciously choose the direction of
the research or engineering that we
practice. This is important because
we believe that we are faced with
a wisdom race, that as technology
becomes more powerful, its impact
can be proportionally greater, either
positively or negatively.
To curb the negative impact, we
need to become wiser individually
(as reflected in our personal decisions) and collectively (through social norms, laws, and regulations).
Unfortunately, technological progress in AI has accelerated faster than
the current rate of progress of personal and social wisdom, ultimately
making it possible for unwise humans or organizations, even those
with good intentions and acting legally, to have large-scale, major destructive effects. This is comparable
to a world in which nuclear bombs
(i.e., very powerful technology) were
accessible and usable by children
(i.e., persons with insufficient maturity and wisdom), which could easily result in global nuclear war. This
highlights the importance of the
discussions still to be had by large
numbers of ML practitioners about
ethics and social impact, as well as
the safeguards that need to be put in
place to protect especially the most
vulnerable members of our society.
We will discuss some of the most
advanced efforts to introduce these
safeguards in the next section, followed by some examples of socially
beneficial applications of ML.

Ethics and AI -
Existing Initiatives
In recent years, there have been numerous initiatives which have taken
one of two major approaches to fostering the ethical practice of AI: (1)
Proposing principles guiding the socially responsible development of AI

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IEEE Technology and Society Magazine - March 2020

Table of Contents for the Digital Edition of IEEE Technology and Society Magazine - March 2020
