Operating Models¶

May 1, 2023
in AI Governance, Operating Models, Organizational Learning
3 min read

Responsible AI needs distributed ownership

Microsoft's chief responsible artificial intelligence officer has published a reflection on the company's program, emphasizing leadership commitment, inclusive governance, and actionable standards. The timing is useful. Generative systems are moving into products rapidly, and many organizations are discovering that an ethics statement does not tell a product team what to do on Tuesday afternoon.

Responsible artificial intelligence (AI) needs a central function. It cannot remain the central function's job alone.

April 5, 2023
in AI Assurance, Product Management, Operating Models
3 min read

AI safety must travel with the product

OpenAI has described its approach to artificial intelligence safety, including pre-release testing, external input, human feedback, monitoring, and phased deployment. The account reflects an important reality: safety is not a property added once to a model and inherited automatically by everything built with it.

Safety has to travel with the product.

March 6, 2023
in Human-Centered AI, Knowledge Strategy, Operating Models
3 min read

Copilots will rewire the handoff

Microsoft has introduced generative artificial intelligence capabilities across Dynamics 365, bringing “copilot” functions into sales, customer service, marketing, and supply-chain work. The examples emphasize drafting emails, summarizing interactions, creating content, and surfacing information inside the applications where people already work.

The most important design question is not how much text a copilot can generate. It is what happens to the handoff.

February 1, 2023
in AI Strategy, Product Management, Operating Models
3 min read

A research preview has become a service

OpenAI has introduced ChatGPT Plus, a paid pilot that promises general access during busy periods, faster responses, and priority access to improvements. The price and feature list will receive most of the attention. The more consequential change is in the relationship between the user and the system.

A research preview invites exploration. A paid service creates expectations.

January 11, 2023
in AI Governance, Operating Models, Knowledge Strategy
3 min read

Responsible AI needs an operating system

Google has opened the year by publishing its most detailed account yet of how it puts artificial intelligence principles into practice. The report covers governance reviews, technical tools, education, and work across product teams. Its value is not that Google has found a universal formula. It is that the report makes a less glamorous truth visible: responsible artificial intelligence (AI) is an operating problem.

Principles matter. They tell an organization what it is trying to protect. But principles do not decide whether a particular use should proceed, determine which test is sufficient, or preserve the evidence behind a difficult exception.