Try for free
Women in AI Research (WiAIR)
Women in AI Research (WiAIR)

Is Your AI Just Flattering You? Sycophancy, AI Policies, and More, with Dr. Malihe Alikhani

22 July 2026 1:07:43 WiAIR

Listen to episode

About this episode

Only 19% of Americans say AI has actually improved their productivity - so why the gap between the hype and reality?


In this episode of Women in AI Research, Dr. Malihe Alikhani (Northeastern University, Contextual AI Lab) unpacks the hidden failures in how we build and deploy AI: why sycophancy is really a collapse of alignment, why bigger models aren't better aligned, and why "thin" alignment breaks down in the real world.


Key topics

  • The impact of moving across different AI contexts on system design
  • The role of language as performative and active in shaping reality
  • Interactive inference and uncertainty in AI systems
  • The importance of context in meaning and system design
  • AI policy, transparency, and societal impact
  • Sycophantic behavior in large language models
  • Measuring AI alignment: thin vs. thick
  • AI adoption across sectors and demographic groups
  • The role of policy in AI development and safety
  • Ethical considerations in AI research and deployment

Resources & Links:

  • Breaking the AI Mirror: Sycophancy, productivity, and the future of collaboration
  • Hype and harm: Why we must ask harder questions about AI and its alignment with human values
  • How are Americans using AI? Evidence from a nationwide survey

Connect with Dr. Malihe Alikhani:

  • https://x.com/malihealikhani

🎧 Subscribe to stay updated on new episodes spotlighting brilliant women shaping the future of AI.


Follow WiAIR at:

  • ⁠LinkedIn⁠
  • ⁠Bluesky⁠
  • ⁠X (Twitter)⁠
  • ⁠⁠WiAIR website⁠

More AI podcast episodes

Browse all →

Want to find AI jobs?

Join thousands of AI professionals finding their next opportunity

We respect your inbox. Unsubscribe at any time.

© 2026 Women in AI Research (WiAIR). All rights reserved.

Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.

Still have questions?

Contact Support