Tackling AI risks: Your reputation is at stake

Danger is all about context

Danger is all about context. The truth is, one of many greatest dangers is failing to acknowledge or perceive your context: That’s why that you must start there when evaluating threat.

That is significantly necessary by way of popularity. Suppose, as an example, about your prospects and their expectations. How may they really feel about interacting with an AI chatbot? How damaging may or not it’s to offer them with false or deceptive info? Possibly minor buyer inconvenience is one thing you possibly can deal with, however what if it has a big well being or monetary influence?

Even when implementing AI appears to make sense, there are clearly some downstream popularity dangers that should be thought of. We’ve spent years speaking in regards to the significance of consumer expertise and being customer-focused: Whereas AI may assist us right here, it may additionally undermine these issues as effectively.

There’s the same query to be requested about your groups. AI could have the capability to drive effectivity and make folks’s work simpler, however used within the mistaken approach it may significantly disrupt present methods of working. The business is speaking loads about developer expertise just lately—it’s one thing I wrote about for this publication—and the selections organizations make about AI want to enhance the experiences of groups, not undermine them.

Within the newest version of the Thoughtworks Know-how Radar—a biannual snapshot of the software program business based mostly on our experiences working with shoppers all over the world—we discuss exactly this level. We name out AI crew assistants as one of the thrilling rising areas in software program engineering, however we additionally observe that the main target must be on enabling groups, not people. “You need to be in search of methods to create AI crew assistants to assist create the ‘10x crew,’ versus a bunch of siloed AI-assisted 10x engineers,” we are saying within the newest report.

Failing to heed the working context of your groups may trigger important reputational injury. Some bullish organizations may see this as half and parcel of innovation—it’s not. It’s displaying potential workers—significantly extremely technical ones—that you simply don’t actually perceive or care in regards to the work they do.

Tackling threat by way of smarter know-how implementation

There are many instruments that can be utilized to assist handle threat. Thoughtworks helped put collectively the Accountable Know-how Playbook, a set of instruments and methods that organizations can use to make extra accountable selections about know-how (not simply AI).

Nevertheless, it’s necessary to notice that managing dangers—significantly these round popularity—requires actual consideration to the specifics of know-how implementation. This was significantly clear in work we did with an assortment of Indian civil society organizations, growing a social welfare chatbot that residents can work together with of their native languages. The dangers right here weren’t in contrast to these mentioned earlier: The context during which the chatbot was getting used (as help for accessing important companies) meant that wrong or “hallucinated” info may cease folks from getting the sources they rely upon.

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