Artificial intelligence is no longer just a staple of the page and movie screen – it is increasingly and creatively used in a variety of real-world contexts. Scientists are using AI to tackle a pressing, worldwide challenges, including an often-overlooked but very serious problem – treating mental health.
Backed by sobering statistics, the world is more aware of the importance of maintaining mental health than ever: the National Institute of Mental Health says that one in five American adults battles mental illness; meanwhile 15.5 percent of the world is afflicted in some way. According to the Henry Kaiser Family Foundation, roughly 40 percent of Americans lack suitable access to mental health professionals. Treatment is expensive when available; specialized treatment often moreso.
AI offers a solution, enhancing the capabilities of human mental health professionals while filling in gaps in treatment. Forbes contributor Bernard Marr recently offered multiple examples of AI’s potential to assist doctors and people alike.
One exciting possibility is to leverage the power of algorithms to analyze patient data. Putting algorithms to work for analysis means the ability to look at amounts of information too massive and impossibly time-consuming for humans to parse on their own, then identifying problems and propose treatment options to fit based on those insights.
The analytic ability could be augmented using chatbots. Humans are already used to interacting with chatbots in a customer service capacity, lending them an air of familiarity. Chatbots would offer the benefit of anonymity, encouraging people to talk more openly and honestly about what they are experiencing, while also offering unparalleled accessibility – not only would a mental health chatbot be accessible at any time, it would give inexpensive (or free) access to mental health services for the people who lack it without physically visiting a doctor’s office.
The possibilities are exciting, but obstacles remain. Algorithmic bias – that is, bias implicit in algorithms that reflects the conscious or subconscious biases of their programs – is a real and potentially damaging phenomenon. Pearl Chiu, a psychologist at the Fralin Biomedical Research Institute at Virginia Tech Carilion, told The Verge that she works to minimize bias by “keeping everyone involved…‘blind to as many things as possible’” – an approach that would need to be standardized and applied in all instances. There is also the issue of developing a truly defined set of parameters for diagnosing mental illness, which is more difficult than diagnosing something based on physical evidence.
These challenges, however, are not a deterrent. Data sharing is being used to increase sample size and limit the possibility of false positives; protocols can be developed to ensure AI tools behave in an unbiased way. A future where AI treats mental health is not farfetched – it is well on its way to becoming reality.
The Investment and Financial Industry Faces the Same A.I.-Driven Revolution
Hedge funds and large institutional investors have been using Artificial Intelligence to analyze large data sets for investment opportunities, and they have also unleashed A.I. on charts to discover patterns and trends. Not only can the A.I. scan thousands of individual securities and cryptocurrencies for patterns and trends, and it generates trade ideas based on what it finds. Hedge funds have had a leg-up on the retail investor for some time now.
Not anymore. Tickeron has launched a new investment platform, and it is designed to give retail investors access to sophisticated AI for a multitude of functions:
And much more. No longer is AI just confined to the biggest hedge funds in the world. It can now be accessed by everyday investors. Learn how on Tickeron.com.