#decisionmaking#bigdata
Speaking of decision making, I watched a TED talk - 3 ways to make better decisions — by thinking like a computer. One take away for me is how to choose a restaurant.
For a classic explore/exploit tradeoff situation, should we go to an old good restaurant or explore somewhere new? Tom Griffiths believed that if you only stay in town for a short period, you don't need to gather information, just choose the old restaurant. But if you gonna stays for a while, you should explore a new place so that the information you get could improve your choices in the future.
The brain of human beings is fascinating. Many researchers study how we think, how we decide and act. There's a 24-year-old MIT student, who has developed wearable tech he can control with his mind. (A New Device Can Hear Your Thoughts)
Big Data
This crazy new mind reader might look creepy, let's look at something also creepy, big data. I feel like almost everyone would talk about big data and machine learning. It becomes something necessary and fundamental. But what I am interested in is how human factors related to big data.
I found one article that tried to figure out human factors engineering and big data analysis. Two of their conclusion are :Big data analytics (BDA) could be useful in the practice of human factors engineering(HFE); HFE could be useful in BDA too.
According to the literature review, the BDA can show new cause-effect correlations in occupational safety which had never been previously described, highlighting possible ergonomic risk groups and supporting decision-making in these areas. Long-standing ergonomics methods can also be driven by big data, and succeed in providing insight into human performance in a novel way. Additionally, data mining and machine learning for extracting key patterns, and for visualization techniques can also related to HFE.
Photo:© istock.com/liuzishan
But even in the age of big data, it’s not only about the technology – it’s also about people. We need people to interpret the outcome of analyses, to scrutinize, to challenge, to agree or disagree, to come up with new or unorthodox ideas. and to discuss.
But even in the age of big data, it’s not only about the technology – it’s also about people. We need people to interpret the outcome of analyses, to scrutinize, to challenge, to agree or disagree, to come up with new or unorthodox ideas. and to discuss. As a human factors engineer, we have the responsibility to think about why and how to wisely use big data.
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