March 24, 2020 This event will highlight the challenges and opportunities in harnessing artificial intelligence (AI) technologies to serve the needs of individuals with disabilities and dependencies. AI can improve the lives of people with disabilities, such as smart devices supporting people with physical disabilities or sight loss. On the other hand, AI outputs can also reflect discriminatory biases present in the underlying data used to develop the algorithms. While this “garbage in, garbage out” principle is well documented in respect to AI and gender or race, it is understudied in respect to disability or dependencies. Interdisciplinary panels of legal scholars, ethicists, AI developers, medical and service providers, and advocates with disabilities/ dependencies will explore best practices and guidelines for stakeholders, guided by ethical principles, legal considerations, and the needs of people with disabilities/ dependencies. Participants will seek to articulate clear criteria for developers and medical providers looking to harness the potential of AI to serve individuals with disabilities/ dependencies, including those whose disabilities/ dependencies are the result of aging, injury, or disease, and the caregivers -- including both professionals and unpaid friends and families -- who support some of these individuals. This webinar was free and open the public. For more information, visit our website at https://petrieflom.law.harvard.edu/events/details/artificial-intelligence-and-disability-dependency

1. AI AND LONG-TERM
HEALTH PREDICTIONS:
LEGAL & ETHICAL
CONCERNS
PROFESSOR SHARONA HOFFMAN
CASE WESTERN RESERVE UNIVERSITY SCHOOL OF
LAW

2. PREDICTIVE HEALTH ANALYTICS SOURCES
• ELECTRONIC HEALTH RECORDS
• PHYSIOLOGICAL EXAMS
• HEALTH INSURANCE CLAIMS
• PURCHASING RECORDS
• WEARABLES
• SOCIAL MEDIA

3. DATA BROKERS
• ACXIOM, LEXISNEXIS
• NOT GOVERNED BY HIPAA
• CAN GATHER, PROCESS, & SELL YOUR
INFORMATION TO ANY INTERESTED THIRD PARTY

4. LONG-TERM PREDICTIONS
• HEART DISEASE , STROKE
• DIABETES, CANCER RECURRENCE
• COGNITIVE DECLINE, DEPRESSION
• FUTURE OPIOID ABUSE
• PSYCHOSIS, SUICIDE

5. LONG-TERM PREDICTIONS COULD BE
INCLUDED IN EHR
• VIEWED BY ANYONE WITH ACCESS TO YOUR
RECORD FOR TREATMENT, PAYMENT, OR HEALTH
CARE OPERATIONS PURPOSES
• VIEWED BY ANYONE YOU AUTHORIZE TO ACCESS
YOUR EHR (E.G. EMPLOYERS, LIFE INSURERS)

6. PREDICTIVE HEALTH ANALYTICS CONCERNS
• PRIVACY
• DISCRIMINATION BY EMPLOYERS, INSURERS
• PSYCHOLOGICAL HARMS
• ERRONEOUS PREDICTIONS

7. STATUTORY REVISIONS
• HIPAA PRIVACY AND SECURITY RULES
• EXPAND DEFINITION OF COVERED ENTITY
• THE AMERICANS WITH DISABILITIES ACT
• COVER INDIVIDUALS WHO ARE REGARDED AS LIKELY
TO DEVELOP PHYSICAL OR MENTAL IMPAIRMENTS IN
THE FUTURE

8. OTHER RECOMMENDATIONS
• CLINICAL PRACTICE GUIDELINES AS TO AI USE
• CAREFUL VALIDATION OF ALGORITHMS
• COUNSELING FOR PATIENTS WHO CONSIDER
PURSUING AI-BASED LONG-TERM PREDICTIONS