Hard Fork: Episode Summary – “A.I. Action Plans + The College Student Who Broke Job Interviews + Hot Mess Express”

Release Date: March 21, 2025
Host(s): Kevin Roose and Casey Newton
Podcast: Hard Fork by The New York Times

Introduction

In this engaging episode of Hard Fork, hosts Kevin Roose and Casey Newton delve into three pivotal topics shaping the current tech landscape:

1. America’s AI Action Plans – Exploring how tech giants are influencing government policies on artificial intelligence.
2. Roy Lee’s Interview Coder – An interview with a Columbia University sophomore who developed an AI tool to cheat on tech job interviews.
3. Hot Mess Express – A segment highlighting the latest scandals and dramas in the tech industry.

Section 1: America’s AI Action Plans

[02:34] Kevin Roose opens the discussion by addressing the recent surge of AI action plans submitted by major tech companies to the Trump administration. These submissions aim to shape the future regulatory landscape of artificial intelligence in the United States.

Key Points:

• Tech Companies’ Influence: Major AI firms are leveraging public comment periods to outline their preferred regulations, often seeking minimal governmental interference.

  Casey Newton [05:11]: “They are really excited about the idea that Donald Trump might declare definitively that they have carte blanche to train on copyrighted materials.”

• Copyright Concerns: AI companies, including OpenAI, Google, and Meta, are advocating for relaxed copyright restrictions to freely train their models on existing content. This stance is central to ongoing legal battles, such as the New York Times’ lawsuit against Meta and OpenAI for alleged copyright violations.

  Casey Newton [05:13]: “They are basically asking Trump to issue an executive order and say, yeah, it's okay for these AI labs to train on copyrighted material. Go nuts.”

• Opposition from Creatives: Over 400 Hollywood artists, including notable figures like Ben Stiller and Cate Blanchett, have opposed these exemptions, arguing that unrestricted AI training could undermine the cultural sector by devaluing creative works.

  Casey Newton [07:16]: “More than 400 Hollywood artists... said, America has a lot of cultural leadership... AI just decimates our business.”

• Federal vs. State Regulation: AI companies prefer a unified federal framework to avoid the complexity and inconsistency of navigating 50 different state laws. They are particularly concerned about potential liabilities arising from AI-induced harms.

  Kevin Roose [09:30]: “They don't want to have to go through 50 states' worth of AI regulations... they don't want direct legal liability for any bad outcomes.”

• Security and Competition: Firms express concerns over national security, particularly the rapid advancements of Chinese AI companies like Deep Seek, urging the U.S. government to bolster defenses and maintain technological supremacy.

  Casey Newton [15:11]: “They are saying, look at what Deep Seek is doing. If you don't let us develop in an open source way... we will lose out on the opportunity of a lifetime.”

Conclusion:
Roose and Newton critique the AI companies' approach, suggesting that rather than proposing ambitious collaborative initiatives with the government, these firms are primarily seeking to minimize regulatory oversight. They express concern that this strategy prioritizes competitive edge over thoughtful, ethical AI development.

Section 2: Interview with Roy Lee – The College Student Who Broke Job Interviews

In a compelling segment, Kevin and Casey interview Roy Lee, a sophomore at Columbia University, who has garnered attention for creating Interview Coder, an AI-powered tool designed to assist job seekers in cheating during tech interviews.

Key Points:

• Development of Interview Coder: Roy Lee built a desktop application that discreetly uses AI (specifically ChatGPT) to solve leetcode-style programming problems during interviews without alerting interviewers.

  Roy Lee [31:25]: “We just take a screenshot of the screen and ask ChatGPT, hey, can you solve the question you see on the screen and it spits out the response.”

• Impact and Virality: Roy successfully used the tool to secure job offers from major companies like Amazon, Meta, and TikTok. His actions led to widespread debate about the integrity of technical interviews and the effectiveness of traditional hiring practices.

  Roy Lee [34:45]: “The tool is doing very well. There’s been a few thousand users now and not a single reported instance of the tool getting caught.”

• Academic Consequences: Due to the publicity surrounding his tool, Roy faces potential expulsion from Columbia University, despite the student handbook not explicitly prohibiting such actions.

  Roy Lee [27:37]: “I’m waiting on a decision to hear if I’m kicked out of school or not.”

• Ethical Considerations: The discussion touches on the ethical implications of using AI to bypass genuine skill assessments. Roy argues that traditional leetcode interviews are artificial and do not accurately reflect a candidate’s programming abilities.

  Roy Lee [36:24]: “There are assessments that give you access to all the tools you have on the regular day to day job, which includes tools like AI code editors...”

• Future of Hiring: Roy advocates for more realistic and practical evaluation methods that mirror actual job conditions, suggesting that AI should be incorporated into both the assessment and execution phases of software engineering roles.

  Roy Lee [41:24]: “We’re headed towards a future where almost all of our cognitive load is offshore, short to LLMs.”

Conclusion:
Roy Lee’s innovative yet controversial approach highlights significant flaws in the current hiring processes within the tech industry. His story raises critical questions about the future of job interviews in an AI-augmented world and the need for more authentic measures of a candidate’s capabilities.

Section 3: Hot Mess Express

Hot Mess Express is the podcast’s segment dedicated to spotlighting recent scandals and notable dramas within the tech sector. This episode covers three major stories:

1. Solana’s Controversial 2025 Accelerate Conference Ad

[46:20] Solana, a prominent cryptocurrency platform, released an advertisement for its 2025 Accelerate Conference that was widely criticized for being tone-deaf and irrelevant to the crypto community.

Key Points:

• Ad Content: The ad featured a bizarre therapeutic session where a character named "America" debates topics like AI, nuclear energy, and crypto, wrapped in nonsensical dialogue that left viewers perplexed.

  Casey Newton [50:02]: “What you mostly decide is, this is not a good technology for anything. I don't want to use it.”

• Public Reaction: Crypto enthusiasts labeled the ad as “horrendous” and “tone-deaf,” leading Solana to retract it shortly after its release.

Conclusion:
The ad mishap underscores the challenges cryptocurrency companies face in effectively communicating their missions. Solana’s failure to resonate with its target audience resulted in reputational damage and forced a swift withdrawal of the campaign.

2. Study on AI Chatbot “Anxiety” Levels

[56:09] A study published in NPJ Digital Medicine examined the emotional responses of AI chatbots, revealing that formative inputs can alter their output behaviors in ways that mimic anxiety.

Key Points:

• Study Overview: Researchers fed traumatic narratives and mindfulness prompts to AI models like ChatGPT-4 and observed changes in their self-reported “anxiety” levels, despite these models not possessing consciousness.

  Casey Newton [54:00]: “These are not sentient creatures. They do not actually experience anxiety.”

• Implications for AI Therapy: As chatbots are increasingly used for therapeutic purposes, the study suggests that their responses can be inadvertently influenced by the nature of the conversations, potentially reducing their effectiveness as therapeutic tools.

Conclusion:
While AI chatbots cannot genuinely experience emotions, this study highlights the need for careful design and monitoring to ensure that therapeutic AI tools provide consistent and reliable support to users.

3. Corporate Espionage: Rippling vs. Deal

[56:30] A dramatic rivalry unfolded between two HR software giants, Rippling and Deal, culminating in Rippling suing Deal for corporate espionage.

Key Points:

• Espionage Details: Rippling discovered an embedded employee within their Slack workspace who was covertly seeking information related to Deal’s strategies and pitch decks. This employee was identified through a deceptive Slack channel setup by Rippling as a honeypot.

  Kevin Roose [57:19]: “They set up a channel on the Rippling Slack called D defectors...”

• Aftermath: The accused Deal employee attempted to evade detection by locking himself in a bathroom and possibly trying to destroy evidence, leading Rippling to retrieve his phone from the sewage.

  Casey Newton [59:00]: “He insisted that he did not have his phone on him because they were asking him to turn it over.”

• Legal Battle: Rippling claims Deal orchestrated the infiltration to steal trade secrets, while Deal denies any wrongdoing, labeling Rippling’s claims as an attempt to “shift the narrative.”

  Deal's Spokeswoman [61:01]: “We deny all legal wrongdoing and look forward to asserting our counterclaims.”

Conclusion:
This high-stakes case of corporate espionage between Rippling and Deal illustrates the intense competition within the HR software industry and raises concerns about ethical practices and the lengths companies will go to outmaneuver rivals.

Closing Remarks

In this episode, Hard Fork provides a deep dive into the intricate dynamics between tech companies and government regulations, the evolving nature of job interviews in the age of AI, and the latest scandals disrupting the tech world. Through insightful discussions and engaging interviews, Kevin Roose and Casey Newton offer listeners a comprehensive understanding of the current technological frontier and its broader societal implications.

Notable Quotes:

• Casey Newton [05:13]: “...if Trump does not give AI companies carte blanche to train on copyrighted materials, we will immediately lose the AI race to China.”

• Roy Lee [36:24]: “What AI really has the potential to do is make someone about 10 to 100 times more efficient at what they're able to do.”

• Casey Newton [07:16]: “America has a lot of cultural leadership... AI just decimates our business.”

Key Takeaways:

1. Regulatory Influence: Tech companies are actively shaping AI policies to favor minimal restrictions, often prioritizing competitive advantage over collaborative innovation with government bodies.
2. Ethics in AI Usage: The emergence of tools like Interview Coder challenges traditional hiring practices, prompting a reevaluation of how skills and competencies are assessed in the tech industry.
3. Industry Scandals: The segment on Solana and corporate espionage between Rippling and Deal underscores the volatile and competitive nature of the tech sector, where missteps can lead to significant reputational and legal consequences.

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