The Role of AI in Mental Health

Low poly brain or Artificial intelligence concept. Symbol of Wisdom point. Abstract vector image of a human brain. Low Polygonal wireframe blue illustration on dark background. Lines and dots.


Artificial Intelligence (AI) holds the promise of transforming virtually any industry, including healthcare. Doctors are already using systems that leverage AI to help them make better decisions and automate tasks, yet this is just the beginning. Over time, consumers and end users will see the benefits of these algorithms — and those benefits will extend over time to the fields of healthcare, medicine, and mental health.

  • AI has transformed how financial institutions manage the risk of investments, and decisions to provide credit to someone or not.
  • AI has transformed manufacturing by predicting when mechanical parts may fail or predicting forecasts based on ever-changing global environments.
  • AI has transformed eCommerce by predicting customer purchasing decisions and understanding the customer intent by analyzing a multitude of data about the customer.
  • AI has improved how WiFi networks can be explained/managed, for example, by predicting what would be the result of the Speed Test if a device on the network performed this test, at any given time.
  • The accuracy of an AI system to assess the risk of extending credit to someone can be measured by whether the person defaulted on the credit or not (binary)
  • The accuracy of an AI system to predict mechanical part failures can be measured by whether the part fails after some time or not (binary)
  • The accuracy of an AI system to predict whether a customer will purchase a product or not can be measured by the purchase decision (binary)
  • Transcription software accuracy can be measured by someone who reads the transcription and listens to the recording (binary)
  • The accuracy of speed test prediction can be measured against an actual speed test

“As we develop algorithms and systems to fine-tune and optimize pattern matching and predictions of what can happen next given a certain environment, we will gain more confidence in these algorithms.”

Predicting Anxiety and Depression

Effects of Drugs

Predicting Addiction

Addiction to drugs or medications is a huge problem in the U.S. While there are ways for people to receive support in dealing with addiction, including recovery centers, individual and group therapy sessions, it’s extremely easy to relapse. Experiencing relapse can be demotivating and put the patient at an even greater disadvantage in overcoming addiction. It can be helpful if the patient has the tools to know what activities or experiences are likely to cause relapse, or what activities can help them stave off relapse (e.g. more exercise, a different diet, more sleep). AI can help in predicting these cause-and-effect scenarios and provide an individualized view. These systems can also alert the treating doctors and clinicians to reach out to the individual at the time of highest risk of relapse and provide the necessary support and help.

Empowering Caregivers


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