Wikipedia was initially dismissed by academia as unreliable. Over 15 years, its decentralized, community-driven model built immense trust, making it a universally accepted source of truth. This journey from skepticism to indispensability may serve as a blueprint for how society ultimately embraces and integrates artificial intelligence.

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The "generative" label on AI is misleading. Its true power for daily knowledge work lies not in creating artifacts, but in its superhuman ability to read, comprehend, and synthesize vast amounts of information—a far more frequent and fundamental task than writing.

Companies can build authority and community by transparently sharing the specific third-party AI agents and tools they use for core operations. This "open source" approach to the operational stack serves as a high-value, practical playbook for others in the ecosystem, building trust.

In its largest user study, OpenAI's research team frames AI not just as a product but as a fundamental utility, stating its belief that "access to AI should be treated as a basic right." This perspective signals a long-term ambition for AI to become as integral to society as electricity or internet access.

The most profound innovations in history, like vaccines, PCs, and air travel, distributed value broadly to society rather than being captured by a few corporations. AI could follow this pattern, benefiting the public more than a handful of tech giants, especially with geopolitical pressures forcing commoditization.

To effectively leverage AI, treat it as a new team member. Take its suggestions seriously and give it the best opportunity to contribute. However, just like with a human colleague, you must apply a critical filter, question its output, and ultimately remain accountable for the final result.

In 2015-2016, major tech companies actively avoided the term "AI," fearing it was tainted from previous "AI winters." It wasn't until around 2017 that branding as an "AI company" became a positive signal, highlighting the incredible speed of the recent AI revolution and shift in public perception.

AI will create negative consequences, like the internet spawned the dark web. However, its potential to solve major problems like disease and energy scarcity makes its development a net positive for society, justifying the risks that must be managed along the way.

Unlike consumer chatbots, AlphaSense's AI is designed for verification in high-stakes environments. The UI makes it easy to see the source documents for every claim in a generated summary. This focus on traceable citations is crucial for building the user confidence required for multi-billion dollar decisions.

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.

Treating AI alignment as a one-time problem to be solved is a fundamental error. True alignment, like in human relationships, is a dynamic, ongoing process of learning and renegotiation. The goal isn't to reach a fixed state but to build systems capable of participating in this continuous process of re-knitting the social fabric.