Ethics and Machine Learning Villanova University Machine Learning Project

Ethics and Machine Learning Why Ethics? Machine learning systems can raise ethical questions. Some of these are new, interesting issues, unique to machine learning. More of them are reflections of ethical questions that occur in many environments and circumstances Any decision-making system must face some of these decisions Any system for summarizing, analyzing, or interpreting information requires some assumptions There are not simple answers to these questions; it is worth discussing some of them Villanova University Machine Learning Project Ethics and Machine Learning

Machine Learning Creation Privacy. Not unique to ML, of course, or even to the web. Much greater awareness with the ubiquitous presence of modern systems Who owns your data? Opt-in vs opt-out, can you remove your data? Accuracy Does the machine learning practitioner have an ethical obligation to make sure that the data used for learning are good? Or an obligation to test and properly interpret the effectiveness of the system? Is this different from the ethical requirements for any other software developer? Villanova University Machine Learning Project Ethics and Machine Learning

Ethics and Machine Learning Machine Learning Use Bias For some decision-making in the US there are protected categories. You cannot base a loan decision the applicant’s age, for instance. If the decision is made by a machine-learning based system, such as a decision tree or neural net, the organization is nonetheless responsible for the result Most obvious problem is when the training data themselves incorporate a bias, intentionally or not. (recent example of ML system preferring caucasian pictures?_ Villanova University Machine Learning Project Ethics and Machine Learning

Machine Learning Use For Individuals Privacy again Systems inferring information about individuals which the individual would not reveal Target case Finding, for instance, potential terrorists Accuracy again Does the system take action about individuals based on the output on an ML system? False negatives, false positives One question is what you do with the decision. One solution: allow “desirable” decision, refer “undesirable decision” to a human. EG, making a loan. System can say yes, human has to say no. Villanova University Machine Learning Project Ethics and Machine Learning

Machine Learning Use for Society Widespread use of machine learning systems may have broad-reaching consequences Automation may lead to loss of jobs now captured by machine Intelligent systems may open up new jobs to less skilled employees. Scanners in grocery stores are good examples of both. ML systems may improve overall efficiency of most processes 20-hour work week? Assistive technologies More efficient use of power and other natural resources Villanova University Machine Learning Project Ethics and Machine Learning

Ethics and Machine Learning Some questions How many jobs in the US are “driver”, and could be replaced by a self-driving car? Would you prefer a human or an artificial intelligence making triage decisions in an operating room? Should a person in Spain be able to prevent Google from showing in a search in the US an accurate but outdated negative fact about him? Should a system deciding whether to recommend an antibiotic for a sore throat err in the direction of false positive (unneeded prescription) or false negative (don’t give needed prescription) What about to recommend major surgery? Villanova University Machine Learning Project Ethics and Machine Learning