Flipping Data Asymmetry for Knowledge Workers

Thomas Wendling is an advisor to the Integrated Engineering Blockchain Consortium, a professional systems engineer at Jacobs Engineering, and a cofounder of CoEngineers.io, a blockchain engineering platform cooperative.

An interesting article in The Economist appeared late last week that suggests that data generated by humans is labor and valuable food for artificial intelligence. The article claims that when people use online services, they are in fact data workers. People should be paid when they create this data.

The article was mainly inspired by happenings in social media, particularly the revelations of Cambridge Analytica harvesting user data to microtarget information to affect outcomes of a political nature. The fact that this data is free to big interests to use for any purpose they see fit has outraged many concerned about both privacy and ownership of data.

If there is demand for this data, someone is also willing to pay for it, and a market could be made. Rather than focusing on the injustice of the voracious digital Eye of Sauron, there is a business opportunity hidden deep within this that could completely reverse the data asymmetry that we currently suffer, and increase productivity of businesses that adopt early.

The Economist article defends a noble idea that has big implications for knowledge workers in every industry. To the extent that knowledge can be reduced to data simply through the observance of protocols in communication, knowledge workers could be creators of remunerable data that is just as valuable to analysis by artificial intelligence as data used to score and rank the predilections of consumers. Humans, whose capital is knowledge, may be able to generate data that is far more valuable than mere consumer behavior, if they can agree on a protocol.

According to Wikipedia, “knowledge workers are workers whose main capital is knowledge. Examples include software engineers, physicians, pharmacists, architects, engineers, scientists, design thinkers, public accountants, lawyers, and academics, and any other white-collar workers, whose line of work requires one to think for a living.”

Knowledge work requires a transaction between customer and a vendor, a claimant and a validator, a writer and a peer reviewer, etc.. If these transactions were rendered into some web format, for example something as simple as a publishing platform using an open data structure and market-based remuneration via cryptocurrency, the application of AI to learn and mimic the anthropology of knowledge work could result in a far subtler method of organizing liquid knowledge assets than current knowledge management technologies such as groupware, enterprise portals, workflow systems, or document management systems, will ever be capable of. The terms ‘human resources management’ and ‘knowledge inventory management’ may become the servants of an expiring mode of thought.

As the controversy of ownership of data on the web escalates, it is a great opportunity to become aware that the data we generate, just through our casual behavior on the web, is really extremely valuable. How much more valuable would it be if we did something on the web that really mattered, like knowledge work? Whatever the resolution on how we should get paid for the data we generate, it will serve as a powerful driver to move knowledge work online where it belongs.