Take the AI hype down a notch, says expert Rodney Brooks

Are folks failing to question AI’s capabilities for fear of looking like party poopers?

In 2025, renowned roboticist and artificial intelligence expert Rodney Brooks continues to be a leading voice advocating for realistic expectations around AI capabilities. His perspective, shaped by decades of experience in robotics and AI development, offers a pragmatic counterpoint to widespread technological hyperbole.

Key Analysis: Brooks identifies a concerning trend in tech discourse where professionals avoid questioning AI hype out of fear of appearing technologically pessimistic.

• He coined the term “FOBAWTPALSL” (Fear of Being a Wimpy Techno-Pessimist and Looking Stupid Later) to describe this phenomenon
• This mindset leads to uncritical acceptance of exaggerated claims about AI capabilities
• Large language models, while adept at manipulating text, lack genuine understanding and real-world context

Technical Reality Check: The implementation of AI and robotics advances typically progresses more gradually than popular predictions suggest.

• Physical-world applications face particular challenges and longer development timelines
• Real economic value, not market hype, ultimately drives successful AI adoption
• Key opportunities exist in practical applications like warehouse automation, agriculture, and elder care

Human-AI Integration: Brooks emphasizes the importance of developing AI systems that enhance rather than replace human capabilities.

• Most jobs will likely be augmented by AI rather than fully automated
• Hybrid systems maintaining human oversight show more promise than fully autonomous solutions
• People generally prefer to maintain agency and control in their interactions with technology

Looking Beyond the Hype: Brooks’ measured approach focuses on solving concrete problems rather than chasing technological trends.

• Success in AI development requires grounding in practical applications
• The path forward lies in pragmatic solutions that address real-world challenges
• Current AI capabilities, particularly in language models, often face limitations in real-world applications

Future Implications: The success of AI implementation will likely depend more on thoughtful integration with human capabilities than on achieving full autonomy, suggesting a future where human-AI collaboration becomes increasingly sophisticated while maintaining human agency and oversight.