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The Skynet Effect: How HR Can Best Utilize AI
- 2. Chronic condition prevention and management 2 Reimagining healthcare to be more scalable, engaging and proactive. Conversational member-facing application leveraging Artificial Intelligence coaching and connected devices to create personalized experiences Available anytime, anywhere for all members Supporting all lines of business Solutions to drive: What is Lark? Care Activation Digital companion to clinician-guided support for sustained weight management Weight Management Proprietary and Confidential
- 3. Trusted Partner Created with leading industry experts, Lark has deep experience working with some of the leading employers and health plans in the country and has been recognized across the industry. Baba Shiv, PhD, MBA Behavioral Economics Expert at Stanford University Bob Gabbay, MD, PhD Chief Scientific and Chief Medical Officer for the American Diabetes Association Jo Solet, PhD Cognitive Behavioral Therapy Expert at Harvard Medical School Jonathan Fielding, MD, MPH, MBA Distinguished Professor of Health Policy at the UCLA Fielding School of Public Health Leading Experts 7YEARS IN R&D EMPLOYERS 2000+ CDC Full Recognition Diabetes Prevention Program Provider The World’s First A.I. Healthcare Provider NPI #1114438157 Lark is a member of The American Heart Association Innovator’s Network Deep Experience VC FUNDING $193M Industry Recognition MEMBERS CONTRACTED 30M+
- 4. Member Activation Weight Management What Does Lark Offer? Lark’s solutions span the spectrum of weight loss to cardio-metabolic risk factors, from prevention to clinical care to the full range of weight management. All Solutions Include Connected Devices Wellness Mass Enrollment & Engagement Screening & Early Disease Detection Care Activation Healthy Weight GLP-1 Companion Prevention Heart Health Diabetes Prevention Diabetes Care Hypertension Care Clinician-Guided Step Therapy
- 7. What is AI?
- 8. What are these buzzwords? In short - getting computers to automate tasks in a human-like fashion. Machine Learning is a form of artificial intelligence what is A.I.? what are Large Language Models (LLMs)? Machine learning models trained on huge amounts of text data that are capable of generating text by predicting the likelihood of a word given its context in an inbound text-based request - a subset of Generative AI what is Generative A.I.? A subset of artificial intelligence that uses machine learning techniques to generate new data or content that is similar to a given set of input data what is ChatGPT? ChatGPT is an example of an LLM and really brought LLMs into the public domain. Since its release in November 2022 there have been numerous other similar public releases, notably Anthropic’s Claude, Google Bard, Facebook’s open-source LLaMA 1.0 and 2.0 among MANY others - and it hasn’t even been a year yet!
- 9. Case Studies for AI in the Employer Space
- 10. Proprietary & Confidential HR Administration ▶ Chatbots for Customer/Employee Support ▶ Automated note-taking and documentation ▶ Become an “editor” rather than a “writer” ▶ Generate new ideas: “List 10 non-monetary ideas for employee recognition.” ▶ Policy Writing: “Draft a work-from-home policy for an employee handbook.” ▶ Drafting Training Content: “Draft me an outline for training new managers.” ▶ Data Analytics, including Sentiment Analysis “Tell me the top themes from these employee comments, written at the 8th grade reading level.” AI in People Operations Iveta
- 11. Talent Acquisition ▶ Opportunities ○ Streamlining time and effort: ““Draft a job description for the Chief People Officer of a health technology start-up.” ○ Reducing overhead by automating parts of the hiring process ○ Designing branded campaigns ○ Drafting job simulations ○ Bonus: Study what predicts success on the job ▶ Things to watch out for ○ Increasing bias ○ Depersonalizing the candidate experience ○ Ignoring the personality behind the resume, does not work for all industries ○ Emerging regulation (i.e. New York City law) AI in People Operations Iveta
- 12. Opportunities ▶ Healthcare access and quality uniformity ▶ App-based ○ Care can be accessed from anywhere ○ The safety of their own home ○ Removes shame from walking into a weight center/mental health facility. ○ Removes biases present in traditional care settings ▶ With intentional safeguards in place, can help achieve greater health equity among users Things to watch out for ▶ Can exacerbate biases found in training data set (validation sets) ▶ Can “hallucinate” AI in Healthcare Wesley
- 13. AI in Healthcare and Benefits Wesley Healthcare Access and Equity 24/7 Care Coverage Access whenever, wherever Aid in Patient Treatment As an assistant or a replacement depending on the situation
- 14. Proprietary & Confidential Behavior Change Lifestyle Management Programs ▶ Common Wellness Program Offering ▶ AI Benefits from Lark’s Model (Compared to Human-led Programs) ○ Reach & Accessibility Access to programs anytime, anywhere, 24/7 ○ Health Equity Same quality of experience for all members ○ Social Determinants of Health Remove biases from the care experience ○ Administrative Overhead Right-size for all workforce sizes ○ Personalized Coaches learn more about your each interaction AI in Wellness Programs Iveta
- 15. Current events Model training data is up until a current point so it won’t have access to events past that point in its training data Irrational Confidence Some responses are inaccurate and too confident These are commonly referred to as “hallucinations” Variation in Response Slight changes in prompt can lead to different answers Users can override prompt instructions - hard to control Unknowns Model is only as smart as training data ● Are there certain topics that contain disproportionately incorrect data? ● Are there inherent biases in the data? ● Are there ways to manipulate certain subjects to spit out incorrect answers? Current AI + LLM Limitations
- 17. Considerations and Questions to Ask Wesley ► Consultative and collaborative partnership ► Understand how they trained their model ► Ask about the safety features they have incorporated into their model ► Understand what cost-savings or ROIs you would be receiving compared to human-driven solutions ► Work with legal team | Different Parties
- 18. Effects AI Will Have on Job Availability
- 19. Many tasks and some jobs have already been, and will continue to be replaced by machines/algorithms (and governments need to support those impacted) But many other jobs will be created by the opportunities that emerge from this new technology - think of the entirely new categories of jobs that exist today that did not 20 years ago ● Telemedicine provider (doctors, nurses) ● Social media influencer ● Blockchain analyst ● Big data scientist ● Uber/Lyft driver ● Drone operator ● Online dating profile writers ● Prompt engineers (2023!) The real question is: How do you stay up to date with the emerging technologies and future-proof your own career? Will AI Take Away Jobs? Creativity and innovation will become a premium Iveta
- 21. Thank you
- 22. What to look for in an AI vendor Are they leveraging their own models? Are they building or fine-tuning on top of third party models? Open-Ended: Leveraging probabilistic model output. We don’t know for sure what will be returned, but content has a higher potential to be engaging Pre-Determined: “Hard-coding” a response. We know exactly what will be returned, but it’s harder to customize to individual user needs Look for partners that are conscious of this trade-off, and when to inject “probabilistic” experiences to drive more engagement and value for users, and when to fall back to “determinism” in situations where we need 100% guarantees Balancing “Open-Ended” and “Pre-Determined” Where do they fall in the AI stack? Consult Internal Experts, Legal & Security! Are they deliberate about their evaluation framework? Consultative and collaborative partners Can they measure and prove their impact? This is a rapidly developing space - are they willing to share knowledge, educate, and collaboratively build solutions?