Ethics is how ‘to decide in a morally right way’. Algorithms are usually regarded as something deterministic and mathematical, not to contain ethics: Eratosthenes’ sieve, for example, will give you all prime numbers up to a given maximum. Every other prime-checking algorithm will come to the same solution. A number is prime or not.
But there is a different kind of algorithm that is far more common in our daily life: calculations to find a solution for some task that other people might have done differently and with different outcomes. These algorithms contain value judgments, choices, or decisions made on how to deal with tasks according to social, cultural, or legal rules or personal persuasion. Obvious examples are credit scoring or pricing of a retail offer. However, there are a multitude of hidden ethical algorithms that are far more pervasive. When an ad network’s targeting system selects which ads we see and which we don’t, we might not find that too important. But a search engine deciding what it regards as relevant to us affects the information we see and what we miss. And medical images like MRIs might even affect our life with their many implicit parameters that are not visible to the physician.
There are three basic types of value judgments in algorithms: 1) Choosing a method, 2) Setting parameters, 3) Deciding how to deal with uncertainty and misclassification. All three judgments are quite regularly not made explicit. For many applications, the only way to understand these presumptions is to “open the black box” – hence to hack.
We will present some of these value judgments, discuss their consequences, and propose a cause to deal with them on a personal as well as on a business level.
Business analyst, business developer with a strong analytical mind. Majken has been working with IT, management information, analytics, BI, and DW for 20+ years. Keen on everything data, math, and ‘data driven’ as a management business principle. Data science. BI. All things data.
Joerg Blumtritt is founder and CEO of Datarella, a computational social science startup that delivers mobile analytics, self-tracking solutions, and data science consulting.
After graduating from university with a thesis on machine learning, Joerg started working as a researcher in behavioural sciences, focusing on nonverbal communication. His projects were funded by an EU commission, the German federal government, and the Max Planck Society. He subsequently ran marketing and research teams for TV networks ProSiebenSat.1 and RTL II, and magazine publisher Hubert Burda Media. As European operations officer for Tremor Media, a New York-based video ad network, Joerg was in charge of building its European enterprises. Recently he worked as managing director for MediaCom Germany.
Joerg is founder and chairman of the German Social Media Association (AG Social Media), and is co-author of the Slow Media Manifesto. Joerg blogs about Big Data and the future of social research at beautifuldata.net, and about The Quantified Self at datarella.com.
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