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Wednesday, July 5, 2023
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military veteran depression suicide rates AI machine learning

Military orgs urged to use AI for help defusing suicidality

American war veterans take their own lives at a rate much higher than the civilian average. Might AI help formulate some sort of solution? The week of Independence Day seems a fitting time to consider the possibility.

Col. Michael Hudson, a retired 30-year U.S. Marine, has done exactly that. Taking to the pages of the military newspaper Stars and Stripes, he gives four reasons AI and machine learning (ML) should be tapped more often to help save veterans’ lives. 

1. State-of-the-art AI/ML models trained to analyze extensive datasets and clinical studies can help detect early behavioral warning signs and flag anomalies before a veteran reaches their breaking point.

  • “Too often, the burden is placed on the veteran in need to first self-assess and then seek out help on their own. Now military and veteran organizations can leverage AI/ML technology to more quickly and efficiently identify when a veteran is at early risk, allowing these orgs to intervene before a crisis occurs.”

2. AI and ML can identify service members and veterans who are at the highest risk due to research-informed indicators of worsening stress and depression.

  • “With confidentiality top of mind … the military and VA’s current calendar-based wellness outreach can be enhanced through the application of data and machine learning techniques to prioritize outreach to vulnerable veterans who need help at the time they need it.”

3. By monitoring evidenced-based veteran behaviors, AI/ML can make recommendations and help veterans maintain regular check-ins, schedule appointments and access critical mental health resources.

  • “Currently, many scheduled military wellness checks do not get the full picture of a veteran’s mental health. In addition, in a time when the VA is already incredibly backlogged, appointments can take weeks to schedule. Being able to prioritize sparse resources is another advantage of shifting the burden from the veteran.”

4. Military leaders, VA offices and veterans service organizations need to start thinking of ways to use emerging technologies and innovation to address this complex issue while proactively assisting our nation’s heroes during a time of need.

  • “Veterans and service members continue to sacrifice so much for our country, often putting their physical and mental health on the line. It is time those working with active service members and veterans take the initiative to mitigate risk factors through strong data and analytics so that veterans realize they have options and can access the help they deserve before it’s too late.”

Hudson presently works as VP of insider risk and suicide prevention for the AI-forward risk management company ClearForce.

Read the full piece in Stars and Stripes.

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google bard cloud AI privacy policy

Industry Watcher’s Digest

Buzzworthy developments of the past few days.

  • Anything you say online can and (probably) will be used to help Google train generative AI. The Big Tech heavyweight said as much when it updated its privacy policy this week. Where once Google said it would only use language-based AI for translating text, it now states its intent to use “publicly available information” to help train its AI models as well as “build products and features like Google Translate, Bard and Cloud AI capabilities.” NewsNation coverage here.
     
  • Explainability in medical AI is overrated. That’s one way to paraphrase one opinion of healthcare AI thought leader Marzyeh Ghassemi, PhD. In a recent “Grand Rounds” podcast hosted by NEJM AI, the MIT prof makes the case that explainability can be a “technically squishy” concept as well as a red herring: Sometimes black-box AI produces better outputs. Listen here.
     
  • AI is helping researchers safely induce allergen tolerance in people whose severe allergic reactions are triggered by edible things. The work is happening at the Food Allergy Institute of Long Beach, Calif. “Patients enter the process with [potentially deadly] anaphylaxis,” explains Inderpal Randhawa, MD, founder of the center. “Thanks to the AI-powered Tolerance Induction Program methodology, they leave the program with what we call ‘food freedom.’” Journalistic video here.
     
  • The U.N. Security Council is circling AI. The august body will convene a meeting July 18 to discuss threats the technology could pose to international peace. AP coverage here.
     
  • Only one health app ranks among the ‘most invasive AI apps’ on offer in Apple’s App Store. That would be K Health. The operation compiling the list, Home Security Heroes, independently reviewed 149 apps to see which ones were most aggressive about tracking users’ personal info for marketing purposes. Details here.
     
  • Say hello to the ‘first AI-driven video library for the medical industry.’ The fruit of a partnership between the AI video management company AnyClip (New York) and the medical conference organizer Kenes Group (Tel Aviv), the library lets clinicians and researchers find granular content with simple search steps. Announcement.
     
  • Health insurers have a new AI-based toolkit to help ease their toils. Wisedocs of Toronto says its AI Medical Summary Platform builds on an earlier version to let users quickly synopsize thousands of pages of medical records for fast decision-making on claims and such. Announcement.
     
  • Did you know training a single AI model can suck up more electricity than powering 100-plus U.S. homes for a year? Pymnts.com breaks down the problem, explaining why AI’s thirst for fuel is a growing concern to energy companies and environmentalists alike.  
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