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Data ethics: the new role of data scientists

Eleonora Iotti

For some years now, the debate on data ethics has assumed more and more relevance: just think of new, tightened regulations related to privacy, the debate on the cookieless web and the work of the Data Ethics Board at the World Federation of Advertisers (WFA), who authored the report “Data Ethics: The Rise of Morality in Technology”.

First of all, a step backward: who is a data analyst, the person who first handles user data? What does the Data Analysis Circle do and how should it unfold from an ethical perspective?

The analyst’s job involves carrying out an activity of measuring, collecting and analyzing web data concerning a project, a property or a topic.

The process of data analysis is cyclical: starting with a problem, collecting data, preparing it, analyzing it, presenting the results and finally making informed decisions.

 

Data Analysis Cycle: awareness, ethics and privacy

However, other elements should also be considered in the Data Analysis Cycle: first of all awareness, something that any data analyst should remember when working with data.

Awareness is the ability to be fully present while we are doing something, while we are doing it, through:

  • knowledge of the contexts (not just the clients’ business) but above all of the people, the places, the context;
  • understanding, i.e. asking questions about the quantity, quality and rightness of the data;
  • conscience, i.e. sensitivity, intuition, overall vision.

Awareness implies a mental state that should be as lucid, open and present as possible.

The main topic of reflection regarding the use of data is certainly ethics, not only in the data collection phase – the GDPR is already an example of a much needed  way of dealing with numbers, thus protecting individuals – but precisely because their interpretation should be as objective as possible. For example, it is important to limit as much as possible the “prejudices” and the biases in the interpretation of the data, since they could influence decisions, increasing problems of inequality or exclusion.

Therefore, an urgent question arises: data should be analyzed in favor of people and not vice versa. A change of gear is necessary, we must pause and think that there are people behind every number.

Approaching data today requires a deeper effort: not only quantitative metrics, but also behavioral insights, which are giving us various information. 

As Alessandro Baricco wrote in his book “The Game”, the Internet can be described as an enormous geographical map, where every continent is represented by the great Big Techs,  AI,  and social media.

Every interaction-action that an individual performs in the various “continents” is part of a story that reveals who that person is, why they make certain choices, where they are going, what changes are taking place in society, etc.

From this point of view, the web is a source of social information, which allows us to better understand the mankind and the historical moment we live in: this means that those who master the data hold a huge power in their hands, with big responsibilities that come along :  the responsibility of improving the conditions of human beings, society and the environment that surrounds us.

 

The human factor in data management

“Listening to the data is important…but so is experience and intuition. After all, what is the finest intuition, if not vast amounts of data of all kinds filtered through a human brain rather than a mathematical model?” wrote Andrew Lang, author, thinker and ethnologist of the early Twentieth Century: a humanist who studied humanity and their complexity, their relationships, observing data, behavior patterns, correlations and comparisons between peoples.

Reading data at this higher level takes sensitivity, human intuition and open-mindedness: what a data analyst does should not be a purely mathematical or merely mechanical activity, on the contrary.

Being a data analyst means being privileged observers of new trends and problems that are emerging in society, it means bearing the values for society itself, because through data it is possible to make a contribution to improving people’s lives.

This also generates economic value for companies: consumers, institutions and employees are demanding companies to take social and environmental issues into consideration.

We are talking about ​​CSR, Corporate Social Responsibility, and ESG metrics, concerning Environmental, Social, and Corporate Governance, that nowadays are not only important but necessary, almost mandatory. CSR includes all those interventions aimed at reconciling the profit of the company with the environment and social issues: a policy that combines commercial operations with a particular interest in social and environmental issues, all voluntarily by the company itself.

Therefore, we should therefore add the adjective ‘human’ to the initial data analysis cycle. Because it takes a human to be aware and fully responsible in front of data.