Face-reading AI will be able to detect your politics and IQ, Stanford professor says
Face-reading AI will be able to detect your politics and IQ,
professor says
Professor whose study suggested technology can detect
whether a person is gay or straight says programs will soon reveal traits such
as criminal predisposition
By Sam Levin in San Francisco Tuesday 12 September 2017
03.00 EDT Last modified on Tuesday 12 September 2017 07.59 EDT
Voters have a right to keep their political beliefs
private. But according to some researchers, it won’t be long before a computer
program can accurately guess whether people are liberal or conservative in an
instant. All that will be needed are photos of their faces.
Michal Kosinski – the Stanford University professor who
went viral last week for research suggesting that artificial intelligence (AI)
can detect whether people are gay or straight based on photos – said sexual
orientation was just one of many characteristics that algorithms would be able
to predict through facial recognition.
Using photos, AI will be able to identify people’s
political views, whether they have high IQs, whether they are predisposed to
criminal behavior, whether they have specific personality traits and many other
private, personal details that could carry huge social consequences, he said.
Kosinski outlined the extraordinary and sometimes
disturbing applications of facial detection technology that he expects to see
in the near future, raising complex ethical questions about the erosion of
privacy and the possible misuse of AI to target vulnerable people.
“The face is an observable proxy for a wide range of
factors, like your life history, your development factors, whether you’re
healthy,” he said.
Faces contain a significant amount of information, and
using large datasets of photos, sophisticated computer programs can uncover
trends and learn how to distinguish key traits with a high rate of accuracy.
With Kosinski’s “gaydar” AI, an algorithm used online dating photos to create a
program that could correctly identify sexual orientation 91% of the time with
men and 83% with women, just by reviewing a handful of photos.
Kosinski’s research is highly controversial, and faced a
huge backlash from LGBT rights groups, which argued that the AI was flawed and
that anti-LGBT governments could use this type of software to out gay people
and persecute them. Kosinski and other researchers, however, have argued that
powerful governments and corporations already possess these technological
capabilities and that it is vital to expose possible dangers in an effort to
push for privacy protections and regulatory safeguards, which have not kept
pace with AI.
Kosinski, an assistant professor of organizational
behavior, said he was studying links between facial features and political
preferences, with preliminary results showing that AI is effective at guessing
people’s ideologies based on their faces.
This is probably because political views appear to be
heritable, as research has shown, he said. That means political leanings are
possibly linked to genetics or developmental factors, which could result in
detectable facial differences.
Kosinski said previous studies have found that
conservative politicians tend to be more attractive than liberals, possibly
because good-looking people have more advantages and an easier time getting
ahead in life.
Kosinski said the AI would perform best for people who
are far to the right or left and would be less effective for the large
population of voters in the middle. “A high conservative score … would be a
very reliable prediction that this guy is conservative.”
Kosinski is also known for his controversial work on
psychometric profiling, including using Facebook data to draw inferences about
personality. The data firm Cambridge Analytica has used similar tools to target
voters in support of Donald Trump’s campaign, sparking debate about the use of
personal voter information in campaigns.
Facial recognition may also be used to make inferences
about IQ, said Kosinski, suggesting a future in which schools could use the
results of facial scans when considering prospective students. This application
raises a host of ethical questions, particularly if the AI is purporting to
reveal whether certain children are genetically more intelligent, he said: “We
should be thinking about what to do to make sure we don’t end up in a world
where better genes means a better life.”
Some of Kosinski’s suggestions conjure up the 2002
science-fiction film Minority Report, in which police arrest people before they
have committed crimes based on predictions of future murders. The professor
argued that certain areas of society already function in a similar way.
He cited school counselors intervening when they observe
children who appear to exhibit aggressive behavior. If algorithms could be used
to accurately predict which students need help and early support, that could be
beneficial, he said. “The technologies sound very dangerous and scary on the
surface, but if used properly or ethically, they can really improve our
existence.”
There are, however, growing concerns that AI and facial
recognition technologies are actually relying on biased data and algorithms and
could cause great harm. It is particularly alarming in the context of criminal
justice, where machines could make decisions about people’s lives – such as the
length of a prison sentence or whether to release someone on bail – based on
biased data from a court and policing system that is racially prejudiced at
every step.
Kosinski predicted that with a large volume of facial
images of an individual, an algorithm could easily detect if that person is a
psychopath or has high criminal tendencies. He said this was particularly
concerning given that a propensity for crime does not translate to criminal
actions: “Even people highly disposed to committing a crime are very unlikely
to commit a crime.”
He also cited an example referenced in the Economist –
which first reported the sexual orientation study – that nightclubs and sport
stadiums could face pressure to scan people’s faces before they enter to detect
possible threats of violence.
Kosinski noted that in some ways, this wasn’t much
different from human security guards making subjective decisions about people
they deem too dangerous-looking to enter.
The law generally considers people’s faces to be “public
information”, said Thomas Keenan, professor of environmental design and
computer science at the University of Calgary, noting that regulations have not
caught up with technology: no law establishes when the use of someone’s face to
produce new information rises to the level of privacy invasion.
Keenan said it might take a tragedy to spark reforms,
such as a gay youth being beaten to death because bullies used an algorithm to
out him: “Now, you’re putting people’s lives at risk.”
Even with AI that makes highly accurate predictions,
there is also still a percentage of predictions that will be incorrect.
“You’re going down a very slippery slope,” said Keenan,
“if one in 20 or one in a hundred times … you’re going to be dead wrong.”
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