The hard questions are not data questions

As we think about the future After Capitalism, one tempting approach is to pursue AI, Big Data, and the like to find the answers. Policymakers (and others) are going to continue to be bombarded with proposals for data modernization and digital transformation as the keys to the future. To be clear, these are good and useful things to do, but they are not going to answer the really hard questions about the future, such as what the world After Capitalism could be like.

Let’s turn to one of my favorite books, Heifetz and Linsky’s Leadership on the Line, for support. Their simple but elegant concept is that leadership questions can be sorted in two categories:

• Technical problems: problems for which people have the necessary know-how and procedures > in my words, they require “data”
• Adaptive challenges: require experiments, new discoveries and adjustments; requires learning new ways > in my words, they require “will”

Technical problems have answers that can be derived by finding and processing the necessary  data. AI, Big Data and the like will be tremendously helpful here.  

Meeting an adaptive challenge, however, requires summoning the willpower to address them. It usually means dealing with social, cultural, or political issues. Adaptive challenges require embarking on new approaches, and this will by definition challenge the existing order … challenge the established way of doing things. And this brings in social, cultural, and political questions. Someone or something is typically threatened by new approaches. Blockchain, for instance, portends to be a wonderful technology, that can help us deal with data. But so far, it has struggled to get past the existing order.

Let’s face it. We MUCH prefer technical problems. We can mobilize, organize and get ‘er done. Adaptive challenges, however, are messy and difficult. The result, as Heifetz and Linsky point out, is that we often try to make what are really adaptive challenges into technical problems – with the predictable poor results.

Let’s take our After Capitalism example. Do we need more data about inequality? No. We need the political and social will to address it. We need to decide if we are really willing to redistribute wealth – take from some and give to others. It’s not a data question. Where data can help us is in in designing the redistribution system. That is a technical problem where AI and big data could be really helpful.  

The really difficult questions still involve choices that need to be made by those nettlesome humans — trying to pass the buck to AI and Big Data is not going to work — Andy Hines