AI fears serious, but frontier slowdown unlikely: BMO

Investing.com-- Concerns about artificial intelligence safety were valid, but leading AI labs showed little sign of slowing development, BMO said in a Friday note.

BMO, citing its AI expert, said fears among AI leaders about safety were genuine, given the importance of aligning AI systems with human interests before problems became irreversible.

But the brokerage questioned how committed developers such as Anthropic and OpenAI were to pacing themselves, pointing to their continued releases of increasingly powerful models.

Recent AI-related hacking incidents were largely benign, BMO said. Still, the brokerage warned that bad actors could increasingly exploit open-access models, noting that users had shown an ability to override safeguards and prompt models into misaligned actions.

Concerns over AI safety swirled after Anthropic head Dario Amodei called for a coordinated slowdown in frontier development, citing potential risks from the technology to humanity. Several AI executives supported his proposal, with AI safety also being discussed during a U.S.-China summit this week.

BMO expects the U.S. and China to eventually tighten AI regulation, with both countries focusing on open-source and open-access models rather than closed systems.

Such rules would likely require approval before broader public release of open-access models, the expert said. Both governments had incentives to limit AI openness, a shift he said would strengthen pricing power for closed-source frontier labs including Anthropic and OpenAI.

Token prices were expected to keep falling, boosting usage of AI tools, BMO said. However, prices were likely to bottom out around 2030, after which closed-source providers would raise prices as users grew dependent on their tools.

Meta Platforms’ AI positioning had improved due to better use of its AI harness, BMO said. Even so, the company remained behind frontier leaders such as Anthropic and OpenAI.

BMO stayed bullish on AI hardware, citing rising scarcity of computing power as users recognized AI’s capabilities exceeded earlier expectations.

White-collar job displacement was likely to become meaningful by 2028, the. Blue-collar jobs would be affected later, in the 2030s, a delay BMO attributed to Moravec’s Paradox, which holds that tasks requiring physical dexterity are harder for AI to automate than cognitive ones.

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