What a Trump victory means for AI

Welcome back to a new edition of AI Odyssey!

Sam Altman confirmed that OpenAI bought Chat.com for more than $20 million making it one of the most expensive domains ever sold.

1: Young AI gets free rein with election outcome

The news: With Trump’s victory, AI development in the U.S. is set to move forward with minimal regulation, unlike the stricter oversight Vice President Harris might have enforced. This election outcome means AI will “grow up” in a freer, hands-off environment, reflecting a Republican preference for limited regulation and concerns about Big Tech bias.

Why it matters: AI training is often compared to raising a child — shaping behavior through data and guidelines. With fewer guardrails, AI could develop biases and risks unchecked, particularly around issues like hate speech, misinformation, and discrimination.

Big picture: AI leaders are split on AI’s role. Many, like OpenAI’s Sam Altman, view AI as a force for good, creating abundance and serving human needs. Critics warn that unregulated AI risks civil liberties, discrimination, and even authoritarian misuse.

Zoom out: The race to advance AI, especially against global competitors like China, is central to U.S. policy. Some argue that the U.S. can lead with AI that strengthens democracy and individual rights, rather than compromising them for speed.

Looking ahead: This election may be the last chance for voters to influence AI’s trajectory. By the next election, AI will be further entrenched, potentially beyond the reach of new regulation.

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2: Open-source AI's identity crisis

The news: The tech world is debating the meaning of "open-source" as it applies to AI. While open-source software has long meant free, modifiable code, giants like Meta, with its Llama 3 model, offer “open” AI with restrictions, sparking questions about what qualifies as true open-source AI.

Why it matters: The definition of open-source AI could shape the industry’s future. For tech companies, an open-source label may boost adoption and trust, potentially making them more competitive. But if the label is too restrictive, it might limit the use and evolution of these models.

The big picture: Traditionally, open-source software is free and modifiable by anyone. But training AI models requires vast resources and has unique risks. Companies like Meta restrict certain uses to prevent misuse and protect their investments, yet still want the open-source label.

Looking ahead: As governments weigh regulations, they’ll need to decide how "open" AI can be, balancing control with innovation freedom. The outcome will define who can develop and deploy AI—from small developers to global powerhouses.

3: Instagram’s AI moves to catch teens lying about their age

The news: Meta will soon use AI to spot teens lying about their age on Instagram. A new “adult classifier” will scan profile data—like follower lists and birthday posts—to estimate users' ages, automatically moving under-18 users into teen accounts with added safety features.

Anti-scam tech: To tackle “celeb-bait” scams, Meta is testing facial recognition to detect fake celebrity ads. If flagged, the AI will compare ad images to real profiles and delete confirmed scams.

Privacy concerns: Meta's new facial recognition for account recovery is also stirring privacy worries, but Meta says selfies will be encrypted and deleted after verification.

Creator frustrations: Instagram's quality reduction for less-viewed videos has frustrated smaller creators, who feel it favors already-popular accounts.

4: Employers turn to AI to bridge skills gaps and boost retention

The news: Companies are using AI to assess employee skills, personalize training, and match staff to new roles—all in a bid to boost productivity and retention. Firms like Johnson & Johnson (J&J) and DHL are seeing early success, with AI helping pinpoint skills gaps and suggest training paths for career growth.

Why it matters: AI-driven skills assessment and training offers a cost-effective way for companies to meet evolving workforce needs without relying solely on external hiring. This approach not only reduces hiring costs but also helps retain valuable employees.

The big picture: AI is aiding employers by analyzing data from job roles, activity, and training progress to measure skills and recommend learning opportunities. J&J has a dedicated AI system mapping out 41 “future-ready” skills across the organization, while DHL’s “career marketplace” directs employees to the right training for career advancement.

Challenges ahead: AI-driven assessments are limited by the quality of the data they’re trained on. Experts caution that while AI can process vast amounts of information quickly, it still lacks the nuanced understanding that human judgment brings, especially for high-stakes decisions.

Looking forward: Companies will likely continue refining AI tools for skills development, with human oversight as a safeguard. As more firms adopt similar hybrid approaches, AI could become a key driver in workforce evolution, helping organizations remain agile and competitive.

AI NOTES 🗒️

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