EkaLore has been adding to releases looking at product and policy issues around BAD Projects and their consumption of data. BAD projects are Big Data, AI, or Data Science projects.
In this release, EkaLore looks at some of the issues with gathering consumer-level data for Automated Driver Assistance Software (ADAS) and the resulting projects.
Enterprises have made an assumption that gathering consumer-level data from their software devices is a fair exchange of value for the functionality and features provided in “free” software. Regulatory and legal restrictions have created significant and material penalties for enterprises not respecting the rules and regulations of law in the respective jurisdictions where the enterprises’ software may be running.
BAD Projects often are pitched to rely on the collection, processing, and analysis of the demographics and contexts of high volumes of data. Gathering such a broad collection of data may create risk. That risk exists whether the data was collected unintentionally or for unspecified future needs.
BAD Projects may also cross regulatory, legal, or ethical lines when looking to ‘correlate’ or ‘analyze behavior.’ “De-identification,” “anonymous data,” and other debates are ongoing.
This series outlines 4 lessons regarding data collection in Electric Vehicles. You’ll find those subsequent posts at www.ekalore.com/bad-project-blog
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