Shane Legg observes that non-technical people often recognize AI's general intelligence because it already surpasses them in many areas. In contrast, experts in specific fields tend to believe their domain is too unique to be impacted, underestimating the technology's rapid, exponential progress while clinging to outdated experiences.
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A 2022 study by the Forecasting Research Institute has been reviewed, revealing that top forecasters and AI experts significantly underestimated AI advancements. They assigned single-digit odds to breakthroughs that occurred within two years, proving we are consistently behind the curve in our predictions.
AI's capabilities are highly uneven. Models are already superhuman in specific domains like speaking 150 languages or possessing encyclopedic knowledge. However, they still fail at tasks typical humans find easy, such as continual learning or nuanced visual reasoning like understanding perspective in a photo.
There's an 'eye-watering' gap between how AI experts and the public view AI's benefits. For example, 74% of experts believe AI will boost productivity, compared to only 17% of the public. This massive divergence in perception highlights a major communication and trust challenge for the industry.
A new technology's adoption depends on its fit with a profession's core tasks. Spreadsheets were an immediate revolution for accountants but a minor tool for lawyers. Similarly, generative AI is transformative for coders and marketers but struggles to find a daily use case in many other professions.
AI reverses the long-standing trend of professional hyper-specialization. By providing instant access to specialist knowledge (e.g., coding in an unfamiliar language), AI tools empower individuals to operate as effective generalists. This allows small, agile teams to achieve more without hiring a dedicated expert for every function.
A leading AI expert, Paul Roetzer, reflects that in 2016 he wrongly predicted rapid, widespread AI adoption by 2020. He was wrong about the timeline but found he had actually underestimated AI's eventual transformative effect on business, society, and the economy.
The main barrier to AI's impact is not its technical flaws but the fact that most organizations don't understand what it can actually do. Advanced features like 'deep research' and reasoning models remain unused by over 95% of professionals, leaving immense potential and competitive advantage untapped.
The internet leveled the playing field by making information accessible. AI will do the same for intelligence, making expertise a commodity. The new human differentiator will be the creativity and ability to define and solve novel, previously un-articulable problems.
Many technical leaders initially dismissed generative AI for its failures on simple logical tasks. However, its rapid, tangible improvement over a short period forces a re-evaluation and a crucial mindset shift towards adoption to avoid being left behind.
The most profound near-term shift from AI won't be a single killer app, but rather constant, low-level cognitive support running in the background. Having an AI provide a 'second opinion for everything,' from reviewing contracts to planning social events, will allow people to move faster and with more confidence.
