Resources that were produced by recognizable figures within data analytics, especially those who have contributed greatly to the field.
Author: N/A; Publisher: United Nations News; Publication Year: 2020. The following article discusses how artificial intelligence (AI) development is especially problematic for countries where governments do not have the ability to effectively regulate consumer privacy or misinformation. International AI regulation will probably be necessary to curb the problem. Social media companies are incentivized to supply…
Author: Tristan Harris, Audrey Tang; Publisher: Your Undivided Attention; Publication Year: 2020. The following podcast episode features Audrey Tang, minister of digital affairs in Taiwan. She is a transgender woman that identifies as “post-gender” and the first non-binary person to hold an executive-level position in Taiwan. In this interview, she discusses how she has helped implement greater data transparency in the government and outlines methods…
Author: Tony Sun, Andrew Gaut, Shirlyn Tang, et al.; Publisher: Arxiv; Publication Year: N/A. The following article discusses how despite their success in modeling various applications, natural language processing (NLP) models propagate and may even amplify gender bias found in text corpora. While the study of bias in artificial intelligence is not new, methods to reduce gender bias in NLP are still in their early stages. The authors of this paper…
Author: Ton Reijns, Richard Weurding, Jos Schaffers; Publisher: KPMG International; Publication Year: 2021. The following article discusses how the European Commission and corresponding European Union General Data Protection Regulation (GDPR) laws have established a framework for ethical artificial intelligence (AI) usage, specifically within the insurance industry. The Dutch have adopted and mandated their own set of standards based off these…
Author: Tom Jongen; Publisher: Medium; Publication Year: 2021. The following article discusses how if any company uses customer data to make customer-facing decisions, there are ethical issues that need to be considered. Also, it asks us to consider “When ‘Know Your Customer’ goes too far;” and the issues related to Facebook/Cambridge Analytica political influence scandal from 2016 provide a clear…
Author: Tolga Bolukbasi, Kai-Wei Chang, James Zou, et al.; Publisher: Arxiv; Publication Year: 2016. The following article discusses how machine learning applied blindly runs the risk of amplifying biases in data. Word embedding, a popular framework for representing text data as vectors that has been used in many machine learning and natural language processing tasks, poses such a risk. The authors demonstrate that even word embeddings…
Author: Thorin Klosowski; Publisher: The New York Times, Wirecutter; Publication Year: 2021. The following article points out the massive amount of data that is collected on us daily by all sorts of different companies. These companies sometimes sell this data, and other times the data gets hacked. It pointed out several situations of how data getting leaked is harmful. The article is proposing that is not how it has to be. We could rebuild our internet to…
Author: Rachel Thomas; Publisher: fast.ai; Publication Year: 2021. The following article focuses on some of the ethical considerations not-for-profits need to consider before beginning a data science project. In addition to the general privacy and ethical considerations for profit companies need to consider, there are also issues of paternalism, power imbalance, and emphasizing flashy high tech solutions over proven low-…
Author: Thomas Walle; Publisher: Fobers; Publication Year: 2020. The following article is particularly insightful as it shows the difference between data privacy and data ethics, even though folks have a tendency to use the terms somewhat interchangeably. The article starts by introducing the idea of data privacy and the data privacy legislation that is being passed. The author then states that data privacy is fairly…
Author: Thomas Brewster; Publisher: Forbes; Publication Year: 2015. The following article discusses how for over a year, SilverPush, an Indian firm, was secretly using inaudible sounds that would play through people’s televisions and get picked up by their cell phones. The imperceivable sound would tune during commercials and get picked up by phones that had SilverPush’s technology embedded in various applications…