Weekly Business Insights from Top Ten Business Magazines | Week 306 | Strategy & Business Model Section | 1

Extractive summaries and key takeaways from the articles curated from TOP TEN BUSINESS MAGAZINES to promote informed business decision-making | Week 306 | July 21-27 , 2023

The Ethics of Managing People’s Data

The five issues that matter most 

By Michael Segalla and Dominique Rouziès | Harvard Business Review Magazine | July–August 2023 Issue

Listen to the Extractive Summary of the Article

The ability to encode, store, analyze, and share data creates huge opportunities for companies, which is why they are enthusiastically investing in artificial intelligence even at a time of economic uncertainty. But the need for data opens the door to abuse. Stories abound about how AI-driven decisions discriminate against women and minority members in job recruitment, credit approval, health care diagnoses, and even criminal sentencing, stoking unease about the way data is collected, used, and analyzed. Those fears will only intensify with the use of chatbots.  As these examine new projects that will involve human-provided data or leverage existing databases, companies need to focus on five critical issues:

Provenance.  To understand what can go wrong with sourcing data, consider the case of Clearview AI, a facial-recognition firm that received significant attention in 2021 for collecting photos of people, using them to train facial-recognition algorithms, and then selling access to its database of photos to law enforcement agencies. According to a report by the BBC, “a police officer seeking to identify a suspect [can] upload a photo of a face and find matches in a database of billions of images it has collected from the internet and social media.”  Countries including Australia and France have objected to Clearview’s collection method and ordered the company to cease collecting, processing, and storing facial data.

Purpose.  In a corporate context, data collected for a specific purpose with the consent of human subjects is often used subsequently for some other purpose not communicated to the providers. In reviewing the exploitation of existing data, therefore, a company must establish whether additional consent is required.

Protection.  According to the Identity Theft Resource Center, nearly 2,000 data breaches occurred in the United States in 2021. Even the biggest, most sophisticated tech companies have had tremendous breaches, with the personal details of more than several billion individuals exposed. The situation in Europe, despite some of the most protective laws in the world, is not much better. 

Privacy.  The conundrum that many companies face is making the trade-off between too little and too much anonymization. Too little is unacceptable under most government regulations without informed consent from the individuals involved. Too much may make the data useless for marketing purposes.

Preparation.  How is the data prepared for analysis? How is its accuracy verified or corrected? How are incomplete data sets and missing variables managed? Missing, erroneous, and outlying data can significantly affect the quality of the statistical analysis. But data quality is often poor.  Cleaning data, especially when it is collected from different periods, business units, or countries, can be especially challenging.  

3 key takeaways from the article

1. The ability to encode, store, analyze, and share data creates huge opportunities for companies, which is why they are enthusiastically investing in artificial intelligence even at a time of economic uncertainty. 
2. But the need for data opens the door to abuse. Stories abound about how AI-driven decisions discriminate against women and minority members in job recruitment, credit approval, health care diagnoses, and even criminal sentencing, stoking unease about the way data is collected, used, and analyzed. Those fears will only intensify with the use of chatbots..
3. Companies need to focus on five critical issues: the provenance of the data, the purpose for which it will be used, how it is protected, how the privacy of the data providers is ensured, and how the data is prepared for use.  

Full Article

(Copyright)

Topics:  Data, Ethics, Privacy