Watson, Big Data, and what happens when a supercomputer can answer any question faster than a specialist. The last missing piece in the fully automated puzzle is learning to ask the right questions.
The industry got robots, workflows were streamlined and optimized. And the need for staff was reduced.
Let’s take a look into the future and see what awaits us who work with knowledge-based tasks. More specifically, let’s talk a bit about marketing and user experience design. 2014 / 2015
Dr. Watson
Many of us have probably already heard about IBM’s intelligent Watson, which can take BIG DATA and conclude a lot of things based on vertical knowledge. Such as, “what kind of marketing should I use if I want guaranteed ROI?” That’s not to say Watson doesn’t possess horizontal knowledge. No, that should not be held against “him.” It’s more a question of him operating on a vertical level, meaning he finds a topic and can dive deep into it. Very deep!
Watson is an “open language - question and answer technology” which for many tech enthusiasts is based on a simple understanding of “ask it a question formulated in any way” and it can, through all kinds of BIG DATA, answer which match of information makes the most sense in that context. The computer seems quite smart, and many people call it artificial intelligence. But what it does is still 100% old-fashioned AI. What is revolutionary about Watson is that it can combine many parameters and transform them into a formula and calculate the best outcome based on our documented experience with things and concepts, aka “BIG DATA.”
Where Watson is better than us is in precision, speed, and breadth of knowledge. If Watson were “employed” in a field where it had to compete on specialized knowledge against specialists, both parties would come very close to the same conclusions, as they both base their conclusions on the same knowledge that is already documented, plus or minus their own experiences.
Yes, Watson won Jeopardy against the grandmasters – extremely impressive. Or is it? Are we surprised that a supercomputer today operates in milliseconds and is asked to find broad knowledge in a timely manner?
Watson breaks the barrier by understanding which combinations of ingredients create good taste and which forms of architectural styles we consider to be the most beautiful in 2015 or 2014, as it operates in known territory. Without knowing it, I would assume it can also come up with conclusions based on forecasts, somewhat like DMI’s supercomputers calculate the weather forecast. This is where it starts to get scary. For the next step is that we let the computer calculate what is best for us based on forecasts, and we should trust that it is correct since it uses BIG DATA. So we can already start to put two and two together regarding which professions will become redundant in the future. In a very near future, mind you. The last piece missing in the fully automated puzzle is that we “ask therightquestions.”
If we come with an unclear question, Watson will likely give us a range of options, somewhat like Google, or in the worst case, draw its own conclusion based on what it thinks you mean with your question, somewhat like Google Translate.
But let’s move away from Watson and talk a bit about Watson’s favorite BIG DATA versus human soft values.
In chapter 2, we will discuss data, what makes BIG DATA easy and quick money if one keeps up with the new trends, but also a bit about the threats of only using data.
Moving on to chapter 2: BIG DATA and vertical thinking –>
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