Home AI Tackling AI dangers: Your repute is at stake

Tackling AI dangers: Your repute is at stake

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Tackling AI dangers: Your repute is at stake

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Danger is all about context

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

That is notably essential by way of repute. Suppose, as an illustration, about your clients and their expectations. How may they really feel about interacting with an AI chatbot? How damaging may it’s to offer them with false or deceptive info? Perhaps minor buyer inconvenience is one thing you may 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 repute dangers that should be thought-about. We’ve spent years speaking in regards to the significance of person expertise and being customer-focused: Whereas AI may assist us right here, it may additionally undermine these issues as nicely.

There’s an identical 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 incorrect means 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 choices 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 speak about exactly this level. We name out AI workforce assistants as some of the thrilling rising areas in software program engineering, however we additionally observe that the main focus needs to be on enabling groups, not people. “You need to be searching for methods to create AI workforce assistants to assist create the ‘10x workforce,’ 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 harm. Some bullish organizations may see this as half and parcel of innovation—it’s not. It’s exhibiting potential staff—notably extremely technical ones—that you simply don’t actually perceive or care in regards to the work they do.

Tackling threat by means 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 group of instruments and methods that organizations can use to make extra accountable selections about know-how (not simply AI).

Nonetheless, it’s essential to notice that managing dangers—notably these round repute—requires actual consideration to the specifics of know-how implementation. This was notably clear in work we did with an assortment of Indian civil society organizations, creating 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 through which the chatbot was getting used (as assist for accessing very important companies) meant that incorrect or “hallucinated” info may cease folks from getting the assets they rely upon.

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