Posts Under: PREDICTIVE ANALYTICS

SIIA Releases Issue Brief on Ethical Use of Big Data and Artificial Intelligence

The application of big data analytics has already improved lives in innumerable ways.  It has improved the way teachers instruct students, doctors diagnose and treat patients, lenders find creditworthy customers, financial service companies control money laundering and terrorist financing, and governments deliver services.  It promises even more transformative benefits with self-driving cars and smart cities, and a host of other applications will drive fundamental improvements throughout society and the economy. Government policymakers have worked with developers and users of these advanced analytic techniques to promote and protect these publicly beneficial innovations, and they should continue to do so. In many circumstances, current law and regulation provide an adequate framework for strong public protection.  Most of the legal concerns that animate public discussions can be resolved through strong and vigorous enforcement of rules that apply to advanced and tradi ...

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Model Explanations are Part of Ethical Data Practice

Institutions involved in predictive modeling are using ever more advanced techniques to predict outcomes of interest from credit scoring to facial recognition to spam detection.  Institutions assess the performance of these models through standard measures such as accuracy (the number of correct predictions divided by the total number of predictions) or error rate (the number of incorrect predictions divided by the total number of predictions).  They can in addition assess the fairness of their predictions with respect to vulnerable groups using measures such as predictive parity across groups, statistical parity, or equal error rates. Institutions also face legal and ethical obligations to explain the basis of their consequential decisions to those who are affected, to regulators and to the general public.  The idea is that people have rights based on autonomy and dignity to be able to understand why institutions make the decisions they do. When predictive models are ...

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AI Spotlight: Artificial Intelligence Can Provide Help to Those Who Attempt Suicide

Suicide is ranked as the third leading cause of death among people ages 10 to 14 and second among people ages 15 to 24 according to the Center for Disease Control and Prevention.  Obviously, suicide and depression are a serious problem facing society. People who are contemplating suicide often feel helpless and reach out, but hearing and acting on cries for help doesn’t always happen in time. Tragically, many people who have struggled with depression and/or suicidal thoughts have used social media to post notes about their intentions to take their own lives or even live stream their suicides. In response, Facebook announced a few months ago that it would be taking more initiative in using its platform for social good.  One of Facebook’s tools to aide with suicide prevention is artificial intelligence. Facebook has developed algorithms that recognize patterns in user’s posts to flag them in case they are at risk of committing suicide.  Critics hav ...

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Big Data Saves Lives

One of the striking examples of the social value of the new techniques of data aggregation and analysis is described in Big Data: A Revolution That Will Transform How We Live, Work, and Think by Viktor Mayer-Schonberger and Kenneth Cukier. Big data is a business buzzword, but the underlying reality it describes is real.  The three Vs of big data – variety, velocity and volume – represent the new world in which data in a variety of formats, including unstructured data like video or text, come at a researcher in enormous quantities and in a constantly changing stream.  Add to this new world of data a range of advanced analytical techniques that can detect novel correlations in data without the need for a prior causal hypothesis, and the result is truly something new under the sun – a way to discover unsuspected and unanticipated insights into the world that simply could not have been uncovered with unaided empirical observation.

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