DM_WK10

Overview of this Lecture / week

In this weeks class we will look at how the EU GDPRs has and will be affecting the use of Machine Learning, Data Science and Predictive Analytics. We will also look at Ethics for Data Science, Data Mining, Machine Learning and Artificial Intelligence.

In addition to this topic and the EU GDPRs, the area of Ethics is important. Most of the machine learning related articles in the EU GDPRs is really about Ethics and treating personal data in an appropriate manager.

Although EU GDPR is a law imposed by the EU, it is not just for companies based in Europe. It affect all companies, in every country around the world, that stores or processes data of people who are in the EU.

Additionally there are lots of countries who are looking at implementing and following the EU GDPRs. These include Australia, Canada, etc and even the USA are considering it. That means the EU GDPRs and its impact on machine learning etc is very important.

Additionally we will be faced with many challenges when working in the area of Data Science, Data Mining, Machine Learning and Artificial Intelligence. What might start out as an interesting project or using an interesting technology can quickly develop into a something that may raise Ethical questions. We will explore some of these issues, some of the questions you might be faced, look at some examples and consider some guidelines that you can use in your Data career.

Notes

Click here to download the GDPR and Other Laws notes.

Click here to download the Ethics for ML, DS and Algorithms notes.

 

Videos of Notes

GDPR and Other Laws on use of Machine Learning, Data Science and Algorithms

Ethics fro Machine Learning, Data Science and Algorithms

Be very careful of Facial Recognition

Lab Exercises

Task 1 – Legal & Ethics Situations

What would you do in the following situation by your manager (or their manager) in work. Possible options are listed below. Discuss your option, why you selected it and what are are the legal and ethical considerations you are facing, and those for the company.

          1. Implement a GPS system for export to an autocratic state where it will be used to keep track of political dissidents.
          2. Modify financial software so that selected bank accounts can not be traced by Tax Authorities.
          3. Install on-street facial recognition system that can identify people who should be self-isolating following travel to a COVID high-risk country.
          4. You are part of a team developing a new application. You discover you have full access to the production data. It is a financial company. You start looking up the financial details of all your friends and families. What if you made some changes to the data of one of your family to help them out.
          5. Develop a system that helps combat bots by showing images to users, but also uses user responses to train an AI system without informing the user.
          6. Develop a ML system that calculates and assigns credit scores for a bank which optimizes profit but is likely to deny loans to the poor or certain ethnic groups.
          7. Develop a system what assigns a unionization risk score for a big retail chain by creating an interactive heat map that monitors warehouse workers.
          8. Develop an application that monitors the work patterns of staff. For example, to monitor remote working staff, by capturing their key strokes and taking screen captures/pictures every X seconds.  Or to monitor how people move about a warehouse, tracking their activities, breaks, etc.
          9. You have been asked to use data obtained from another company without their knowledge to enrich the data set for your customer profiling application.

Possible options/answers for these include (their could be other ones) the following. Discuss with other people in the class.

            • Quite happy to do it
            • Reluctant but would dot it
            • Object to doing it and ask for alternative task – but do it if I have to
            • Resign from the job rather than do it
            • Resign from the job and report to the authorities

Task 2 -This is an evolving field

Check out the reading list below and make sure you read most of these articles. You will find that there may be some confusion on what the implications of the laws really mean. But by reading lots of these articles will keep you informed and updated.

Other Videos

60 Minutes Article and Video : Facial and emotional recognition; how one man is advancing artificial intelligence

Books

 

Additional Reading Materials

When Does Predictive Technology Become Unethical?

ACM Code of Ethics and Professional Conduct

Excellent Comic Book on Digital Ethics

Ethics Institute for AI & Machine Learning – Principles

Ethics Use Cases

Doing Good with Data Science – Mike Loukides, Hilary Mason & DJ Patil
Ethical Data Science Is Good Data Science – Steve Touw
Ethics must be at centre of AI technology

EU GDPR  Document
EU GDPR website

The General Data Protection Regulation Matchup Series

Doing Good with Data Science – Mike Loukides, Hilary Mason & DJ Patil
Ethical Data Science Is Good Data Science – Steve Touw
Ethics must be at centre of AI technology

EU GDPR Guidelines for determining whether processing is “likely to result in a high risk” for the purposes of Regulation 2016/679
GDPR and You website
My blog posts on EU GDPR and ML
EU GDPR – The GDPR and all that

Amazon’s AI recruiting tool showed bias against women

6 Countries with GDPR-like Data Privacy Laws