The Pulse
Three things shaping AI in healthcare this fortnight:
Ofcom investigates Elon Musk's X over Grok AI sexual deepfakes — The investigation highlights how generative AI misuse can cause real psychological harm, reinforcing why safeguards, accountability, and consent matter deeply when AI touches identity, intimacy, and trust. (BBC, 2026)
Introducing OpenAI for Healthcare — OpenAI’s healthcare-specific framing signals a shift toward more regulated, domain-aware AI use, acknowledging that clinical environments demand higher standards for safety, privacy, and oversight (OpenAI, 2026)
Transform healthcare from insight to action — Claude’s healthcare focus emphasizes using AI not just to analyze data, but to actively support clinical and operational decisions, highlighting a growing shift toward AI as a participant in workflows rather than a background tool, and raising the stakes for human oversight. (Claude, 2026)
Takeaway: AI is rapidly embedding itself into healthcare systems and social platforms alike, making governance, ethical boundaries, and clinician involvement more urgent than ever.
Psychology & Behavioral Health
AI chatbots and digital companions are reshaping emotional connection (APA, 2026)
AI chatbots are increasingly being experienced as companions, confidants, or emotional supports, particularly among younger users and people facing loneliness. The APA notes that while these tools may offer comfort, they can blur boundaries, reshape attachment patterns, and influence emotional development in ways clinicians are only beginning to understand.
Clinician Cue: Ask clients about their emotional connection to AI with curiosity and care, noting patterns of reliance or unmet needs that would reflect growing attachment and emotional dysregulation.
Building Open-Source AI Models That Emphasize Generating Mental Health Advice (Forbes, 2026)
The article explores efforts to build open-source AI models designed specifically to offer mental health advice, raising concerns about quality control, misuse, and the illusion of clinical authority. While openness may improve transparency, it also lowers barriers for deploying tools that may feel therapeutic without being safe or evidence-based.
Clinician Cue: Help patients distinguish between mental health information and mental health care, and be explicit about the risks of treating AI-generated advice as a substitute for professional support.
Medicine & Clinical Innovation
New AI model predicts disease risk while you sleep (Stanford Medicine, 2026)
Stanford researchers developed an AI model that analyzes sleep data to identify early signals of disease risk, suggesting sleep may be a powerful window into overall health. While promising, the approach depends heavily on data quality, interpretation, and careful clinical validation.
Quick Win: If patients bring in wearable or sleep-tracking data, treat it as a conversation starter, not a diagnosis, and integrate it thoughtfully into broader clinical context.
Your next primary care doctor could be online only, accessed through an AI tool (NPR, 2026)
With primary care shortages growing, AI-driven virtual care models are emerging as stopgaps for triage, monitoring, and basic diagnosis. NPR notes these systems may improve access, but risk fragmenting care if human oversight and continuity are weak.
Quick Win: When working with patients using virtual or AI-mediated care, help them clarify when escalation to a human clinician is needed and how to maintain continuity across systems.
Ethics & Oversight
Policy & Compliance: As AI tools begin to function like clinical intermediaries (triage, guidance, documentation), organizations should clearly define when AI support crosses into regulated clinical activity, and document those boundaries in policy, consent, and workflow design.
Bias & Transparency: Require visibility into what the model is not designed to do (e.g., crisis response, diagnosis, treatment planning) and make those limits explicit to both clinicians and patients to prevent false confidence.
Accountability & Governance: Every AI tool used in care should have a named human owner responsible for oversight, escalation paths, and periodic review of unintended psychological or clinical effects.
Wayde AI Insight
Across this issue, a clear theme emerges: AI has moved beyond analyzing data to shaping decisions, relationships, and expectations of care. From emotionally responsive chatbots to tools integrated into diagnosis and primary care, the technology now feels relational as well as technical. Clinicians should neither reject nor adopt AI without thought, but instead guide how it is used by setting boundaries, clarifying limitations, and emphasizing that trust and accountability remain human. Technology can expand insight, but meaning, safety, and care still rest with clinicians.
Connect
Helping healthcare professionals adopt AI ethically and responsibly.
Produced by Wayde AI with AI assistance.