The Washington Post · 25 Oct, 16:45 · Artificial Intelligence briefing

Opinion | The best defense against bad AI is more good AI

Recent commentary suggests that combating the proliferation of low-quality or harmful artificial intelligence requires the strategic deployment of robust, high-quality AI systems.

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The briefing

The story
in brief.

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Recent commentary suggests that combating the proliferation of low-quality or harmful artificial intelligence requires the strategic deployment of robust, high-quality AI systems. The argument posits that rather than resisting technological advancement, organisations should actively develop superior algorithms and ethical frameworks. This approach aims to crowd out inferior outputs by establishing higher standards for accuracy, reliability, and utility. For professionals, this indicates a shift towards quality control and system integrity over mere adoption speed, emphasising the need for rigorous evaluation metrics in an increasingly automated landscape.

Employer demand for AI Strategy skills — indexed growth since 2019
Indicative index of skill mentions in professional job postings for the field this story moves (2019 = 1)

Your move

What this means
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You must pivot from passive AI consumption to active quality assurance. As organisations prioritise reliable outputs, skills in auditing algorithms and defining ethical boundaries will surge in value. Professionals who can distinguish between superficial automation and substantive intelligence will lead strategic initiatives. You should focus on understanding the technical underpinnings of model reliability and data integrity. Develop expertise in evaluating AI performance against strict criteria, ensuring systems align with business objectives without compromising accuracy. This proactive stance transforms you from a user into a gatekeeper of quality, making you indispensable in navigating the complex landscape of competing AI solutions.

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