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Data Science Ethics & Big Data Business Models

Ray Wang's HBR piece "What a Big-Data Business Model Looks Like" asserts three basic information based models:

1. Differentiation
2. Brokering
3. Delivery Networks
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While Mr. Wang is partially correct, I think "information based" models is overly narrow in concept. I suggest data science and big data will create new business models, improve business and knowledge processes, reduce costs and help better manage risk. On the other hand, data science can be abused for unwarranted advantage and data scientists need to think hard about ethics and a code of conduct to avoid damaging individuals and society. It is disheartening to witness frequent manipulation of data, flawed models and outright intellectual dishonesty.
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We are in the pre-industrial age of data science and data technologies for business, government and individuals. Massive hype of "data science" and "big data" overestimates short term benefits and likely underestimates long term consequences. The hype also underestimates or ignores the potential dark side.
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At this time, modern data analytical technologies and highly specialized data scientists are required to get valuable, actionable insights from data. Those who take advantage experience significant competitive advantage. The playing field is uneven. If we are not careful, information and knowledge inequality will continue to increase to the advantage of "big business" and "big government" creating greater opportunities and probabilities for abuse.
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In the future, data tech and science will be automated, cheap and democratized resulting in massive qualitative change. The Internet of Things (all objects and people tagged and monitored to enable communication and be identified and inventoried by computers), machine learning, improved algorithms and artificial intelligence will be transformative and revolutionary.
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I respectfully suggest that data scientists have a responsibility to society to create and respect an ethical data science professional practice framework in attempt to avoid, detect, measure and remedy data manipulations, flawed models and other data science sins. If we fail, the positive potential of data science for society as a whole could result in dystopia.
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Tags: Big, Business, Data, Ethics, Models

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