We as a society should actively involve a divers, non-tech-audience into the discussion in the proper usage of AI – it can not be tech experts only discuss what our everyday life is impacting so much already.
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Harvard Business Review may have dubbed being a data scientist the “sexiest job of the 21st century”, but that hasn’t necessarily made it easier to find analytics experts. There is still a huge skills gap in data science. Recently I met with Andreas Vermeulen who is Director of Technology and
The Amazon rainforest is the largest rainforest on our planet. Nowhere else in the world can we find more animal and plant species. Unfortunately, we lose on average 800 square kilometres of forest every day to deforestation for logging, agriculture or road construction. But there is still hope for our
Analytics offers huge potential to transform raw data into operational intelligence. It provides new insights into old or new problems. This is crucial in business – but it is even more important for tackling big societal issues, such as domestic violence or human trafficking. I recently had the opportunity to
The process changes that are taking place in the insurance world are massive. More and more insurance companies allow for remote sales of life products and entire sales processes have been simplified for the benefit of the customer. However, opportunities for abuse arose with them as well. A simpler process
"According to Gartner, “over 50% of senior marketing leaders are unimpressed with the results they receive from marketing analytics investments” – yet most companies expect to increase these investments over the next few years. How can we avoid throwing good money after bad?" By Oliver Sheerin, Senior Customer Intelligence Advisor, SAS. When
In my previous article, “The Vital Ingredients of Responsible AI,” I described the principles that underpin the need to develop AI systems that factor in the human factor, not only contribute to business outcomes but also protect individuals, society and the environment. While it’s difficult to argue with those principles,
In my previous article, “The Business Imperative for Responsible AI," I covered the main business drivers for responsible AI. Beyond the greater good and social responsibility, responsible AI is emerging as a key factor for successful AI adoption. In this article, I will describe the main ingredients of responsible AI:
If my experience is anything to go by, there’s a sizeable number of customers that still have SAS workloads running on IBM mainframes. Now I have tremendous respect for S/390 (I can still navigate TSO/ISPF et al. and started my IT career programming in PL/AS on MVS and VM), but
With the steep rise of artificial intelligence (AI) adoption across all facets of society, ethics is proving to be the new frontier of technology. Public awareness, press scrutiny and upcoming regulations are forcing organizations and the data science community to consider the ethical implications of using AI. The need for