Proponents of artificial intelligence solutions need to come forward with a serious public relations effort

2-Color-Design-Hi-Res-100px-widthMachine learning solutions, and those of the “deep learning” variety are playing an ever increasing role in daily computing activities for most people. This condition does not look to change anytime soon.

But regardless, ISVs with products targeted to the predictive analytics market, or the robotics market, or any one of many emerging new market segments, need to tune in on public perception about these technologies in the mature global markets (US, Western Europe, Japan). Public perception has the potential to prod government regulators towards counter-productive pronouncements. Therefore, it makes sense for ISVs to mount a public relations effort to ensure public perception about these technologies stays “on track”.

On Tuesday, February 24, 2015 the Wall Street Journal published an article germaine to this topic. The piece was written by Timothy Aeppel and is titled What Clever Robots Mean for Jobs (http://www NULL.wsj NULL.com/articles/what-clever-robots-mean-for-jobs-1424835002?mod=WSJ_hpp_MIDDLENexttoWhatsNewsThird). The employment theme is a very familiar one for anyone involved with efforts to use computer processes to automate repetitive tasks. So Aeppel’s skepticism about just whether or not an exploding market of robotics solutions will lead to more jobs, or not (which appears to be his position) is really nothing new.

But the timing of the article, in close proximity to several other articles from “prominent” individuals (Bill Gates, Stephen Hawking and more) about the dangers presented by algorithms should they be applied to computing lends power to Aeppel’s thoughts. Readers should also not lose sight of the 2016 Presidential election here in the States, where ostensible candidates like Hillary Clinton are starting to stake out turf about “hi tech” and its performance as a job creator.

I encourage readers to go back to my first points in this post. Methods of automating processes, including requirements for prediction, are increasing and becoming more accessible to “average” consumers of computing services. This is not a bad thing. On the contrary, in my opinion the accessibility of comparatively powerful methods of enhancing the accuracy of prediction is a net positive contribution to overall business and certainly a likely simulant for new business activity.

Do new businesses create jobs? I am not sure as to the answer to this question, but I can posit they certainly empower more entrepreneurs. Machine learning ISVs and their deep learning siblings need to step forward and do a better job of educating the public about the real benefit of these technologies.

Ira Michael Blonder

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