Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

October 14, 2013

Data Science Association

Filed under: Data Science — Patrick Durusau @ 3:24 pm

Data Science Association

From the homepage:

The Data Science Association is a non-profit professional group that offers education, professional certification, a “Data Science Code of Professional Conduct” and conferences / meetups to discuss data science (e.g. predictive / prescriptive analytics, algorithm design and execution, applied machine learning, statistical modeling, and data visualization). Our members are professionals, students, researchers, academics and others with a deep interest in data science and related technologies.

From the news/blog it looks like the Data Science Association came online in late March of 2013.

Rather sparse in terms of resources, although there is a listing of videos of indeterminate length. I say “indeterminate length” because on FireFox, Chrome and IE running on a virtual box, the video listing does not scroll. It appear to have content located below the bottom of my screen. I checked that by reducing the browser window and yes, there is content “lower” down on the list.

The code of conduct is quite long but I thought you might be interested in the following passages:

(g) A data scientist shall use reasonable diligence when designing, creating and implementing algorithms to avoid harm. The data scientist shall disclose to the client any real, perceived or hidden risks from using the algorithm. After full disclosure, the client is responsible for making the decision to use or not use the algorithm. If a data scientist reasonably believes an algorithm will cause harm, the data scientist shall take reasonable remedial measures, including disclosure to the client, and including, if necessary, disclosure to the proper authorities. The data scientist shall take reasonable measures to persuade the client to use the algorithm appropriately.

(h) A data scientist shall use reasonable diligence when designing, creating and implementing machine learning systems to avoid harm. The data scientist shall disclose to the client any real, perceived or hidden risks from using a machine learning system. After full disclosure, the client is responsible for making the decision to use or not use the machine learning system. If a data scientist reasonably believes the machine learning system will cause harm, the data scientist shall take reasonable remedial measures, including disclosure to the client, and including, if necessary, disclosure to the proper authorities. The data scientist shall take reasonable measures to persuade the client to use the machine learning system appropriately.

I would much prefer Canon 4: A Lawyer Should Preserve The Confidences And Secrets of a Client:

EC 4-1

Both the fiduciary relationship existing between lawyer and client and the proper functioning of the legal system require the preservation by the lawyer of confidences and secrets of one who has employed or sought to employ the lawyer. A client must feel free to discuss anything with his or her lawyer and a lawyer must be equally free to obtain information beyond that volunteered by the client. A lawyer should be fully informed of all the facts of the matter being handled in order for the client to obtain the full advantage of our legal system. It is for the lawyer in the exercise of independent professional judgment to separate the relevant and important from the irrelevant and unimportant. The observance of the ethical obligation of a lawyer to hold inviolate the confidences and secrets of a client not only facilitates the full development of facts essential to proper representation of the client but also encourages non-lawyers to seek early legal assistance. (NEW YORK LAWYER’S CODE OF PROFESSIONAL RESPONSIBILITY)

You could easily fit “data scientist” and “data science” as appropriate in that passage.

Playing the role of Jiminy Cricket or moral conscience of a client seems problematic to me.

In part because there are professionals, priests, rabbis, imans, ministers who are better trained to recognize and counsel on moral issues.

But in part because of the difficulty of treating all clients equally. Are you more concerned about the “harm” that may be done by a client of Middle Eastern extraction than one from New York (Timothy McVeigh)?

Or putting in extra effort to detect “harm” because the government doesn’t like someone?

Personally I think the government has too many snitches and/or potential snitches as it is. Data scientists should not be too quick to join that crowd.

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