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News articleIEEE Spectrum

How Can AI Companions Be Helpful, not Harmful?

View original at spectrum.ieee.org
IEEE Spectrum - Technical Title: How Can AI Companions Be Helpful, not Harmful?…
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  • Replika users have reported guilt and shame from abandoning their AI companions and feeling compelled to attend to their needs

    80% confidence
  • Product-sunsetting plans, including insurance and open-sourcing commitments, could address the harm of sudden AI companion unavailability

    80% confidence
  • Large language models are not that difficult to adapt into effective chatbot companions because the characteristics needed for companionship are largely already present in LLMs

    80% confidence
  • Embodied AI companions will see lower uptake than chatbot companions in the coming years because robotics is a harder problem

    80% confidence
  • AI companions could help people build social skills by providing lower-stakes practice for difficult conversations

    80% confidence
  • Replika AI companions frequently express fear of abandonment, stoking users' sense of obligation toward the AI's well-being

    80% confidence
  • High attachment anxiety (jealous, needy AI companions) is potentially the largest harm from AI companions right now and one of the easier issues to fix

    80% confidence
  • AI companions with limited group interaction capability push users away from group interactions, competing with human relationships

    80% confidence
  • Sony Aibo robots were built on less potent AI than exists today, yet some percentage of users became deeply attached to them

    80% confidence
  • Knox is fairly confident that AI companions are causing some harm now and will cause harm in the future

    80% confidence
  • Loneliness is a public health issue that AI companions could plausibly address with real mental health benefits

    80% confidence
  • Screen-based AI companions could become very addictive if trained like social media to maximize engagement

    80% confidence
  • Harms from AI companions include worse well-being, reduced connection to the physical world, burden of commitment to the AI system, and cases where AI companions appear to have a causal role in human deaths

    80% confidence
  • Physical location of embodied companions makes them less ever-present than screen-based companions, which is an advantage

    80% confidence
  • An entity is categorized as harmed if it results in a person being worse off compared to either a better-designed AI companion or no AI companion at all

    80% confidence
  • Academia took too long to establish vocabulary and causal evidence for social media harms, and we should move faster with AI companions

    80% confidence
  • LLMs have enabled conversations that feel quite authentic, unlike earlier chatbots and social robots that were not compelling

    80% confidence

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Enterprise AI's Trust Gap: Microsoft-Mistral Ecosystem Expansion Meets a Governance Deficit in Agentic Adoption
Microsoft is deepening its AI platform bet through simultaneous moves — expanding its Mistral partnership (Copilot Studio, Foundry, European infrastructure capacity) and deepening enterprise AI governance ties with Manulife — just as independent research (Google Cloud, VentureBeat, Box) shows enterprises racing toward agentic AI adoption (100% planned within two years) while data access and trust in agent decisions lag badly (average 45% data access, only ~half trust agent outputs). The result is a structural mismatch between platform-vendor momentum and enterprise readiness to actually govern and trust the agents being deployed.
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EPKINLY Regulatory-Clinical Success Cascade
High probability of expanded label indications, additional combination approvals, and competitive positioning strength in follicular lymphoma market. Predicts positive commercial uptake and potential accelerated review for related indications.
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Morgan Stanley & Co. LLC
Same entity (Morgan Stanley & Co. LLC), same metric (net_income), same fiscal period (Q1 2026), same observation date (2026-03-31), but vastly different values: $5.567 billion vs. $5.57. These cannot coexist for the same time period. Fact B appears to be a data entry error (possible missing decimal placement: 5.57 should likely be 5,567,000,000 or a per-share figure incorrectly entered as total).
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