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Artificial Intelligence

Artificial intelligence (AI), sometimes known as machine intelligence, refers to the ability of computers to perform human-like feats of cognition including learning, problem-solving, perception, decision-making, and speech and language.

Early AI systems had the ability to defeat a world chess champion, map streets, and compose music. Thanks to more advanced algorithms, data volumes, and computer power and storage, AI evolved and expanded to include more sophisticated applications, such as self-driving cars, improved fraud detection, and “personal assistants” like Siri and Alexa.

Today, researchers are using AI to improve predictions, diagnoses, and treatments for mental illnesses. The intersection of machine learning and computational psychiatry is rapidly creating more precise, personalized mental health care.

Artificial Intelligence Now and In the Future

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Artificial intelligence as it is used today is considered “weak AI,” because it is generally designed to perform just one or two specific tasks as well as, and often better than, humans. At this point, however, the controversial future of AI research includes ideas about developing “strong AI,” or a super-intelligence, with the potential to perform many or all cognitive tasks better than humans. AI safety research is a priority for some scientists concerned about potential dangers if such advanced technology gets into the wrong hands, although others still question the possibility of ever achieving human-level strong AI.

How is AI being integrated into daily life?

People often possess an array of devices that incorporate artificial intelligence. For example, devices that leverage centralized home-management systems adjust thermostats. Wearable gadgets push their users to exercise or consider their food choices. Smartphones and tablets complete words and sentences as people type emails and texts. Autonomous vehicles are already in use on city streets.

How is AI being integrated into the workforce?

Machines have already transformed the jobs of millions of people—by monitoring actions that couldn't previously be tracked, calculating data in new ways, guiding decision making, or taking over tasks. For example, drones photograph and monitor some construction sites for discrepancies. Some probation officers handle their cases according to instructions from a computer program, which decides how much of a risk each person poses. Algorithms write reports for some publications.

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Artificial Intelligence and Mental Health

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Artificial intelligence has the potential to reshape psychiatry—and those efforts are already well underway. Amassing massive datasets can allow scientists to identify factors that render people more vulnerable to mental illness, improve the accuracy of diagnoses, and assess which treatments are effective and for whom.

The field of computational psychiatry leverages mathematical and computational tools to improve the understanding, diagnosis, and treatment of mental disorders.

What information could AI provide about mental health?

Computational psychiatry has the potential to gain insight into any condition with a large enough dataset. Machine learning could identify which genes contribute to the development of autism or the factors that render adolescents vulnerable to binge-drinking such as brain size or parental divorce. These programs could reveal which systems are affected by dopamine in patients with Parkinson’s disease, or a person’s risk for depression based on factors such as sex and childhood trauma.

Could AI help diagnose bipolar disorder?

Artificial intelligence has the potential to leverage large datasets to improve diagnoses and reduce misdiagnoses. For example, depressive episodes in bipolar disorder and depression can be difficult to distinguish; many patients with bipolar are misdiagnosed with major depressive disorder. A machine learning algorithm that used self-reports and blood samples recently identified bipolar disorder patients in various scenarios, potentially providing a helpful supplement for clinicians in the future.

The Ethics of Artificial Intelligence

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The evolution of artificial intelligence has led to countless ethical questions. Will machine learning perpetuate bias and inequality? Will AI infringe on human privacy and freedoms? Will humans lose their jobs to robots? Will machines become more intelligent than humans?

People are right to question the nature of machines that can evolve on their own. By actively engaging with these concerns, hopefully humans can develop ethical systems of artificial intelligence moving forward.

Why does the technology sector pose unique ethical challenges?

People interact with technology on an unprecedented scale and in many different environments—at work, in the supermarket, in the car, at home. Technology deployers have some responsibility to keep people safe as AI poses ethical challenges. Whether it’s anticipating systemic bias, recognizing when technologies coerce decision-making, intercepting malicious actors who wish to weaponize platforms, or taking a stand on overzealous surveillance, creators and consumers need to make sure that technology serves the population well.

What are some underappreciated ethical concerns about AI?

One ethical concern about artificial intelligence is the potent yet subtle influence of technology on people’s choices and decision-making. Companies are able to use all of the information they store about people to their advantage—“nudging” people towards decisions that are predominantly in the company’s interests. Another concern may arise from the technologies that claim to be able to read and interpret human emotions. The idea of a product deceiving a child or vulnerable adult into believing it truly “understands them,” and thereby influencing them, is worrying.

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