Greetings from Dataspace!

The last edition of our newsletter focused on some very creative applications of data science tools and methods. Most of these were lighthearted, merely reflecting the interest of the creators in their subject matter – like true scientists, they applied their skills to the questions that interested them.

In contrast, today’s newsletter delves into some of the data science “grey areas” – uses and applications that raise ethical and legal questions that need to be carefully considered.

To start off in the most general sense, we need to be aware of the variety of spaces where the questions of ethical usage of data science tools have come into play. Similarly, it is important to recognize that we may hold some problematic preconceptions that can present roadblocks to truly productive discussions of ethics and technology.

The good news is that these questions of ethics are, in fact, being raised. While certainly not all-inclusive, the below list highlights some of the most salient areas of data science usage that are currently under scrutiny:

Facial Recognition:  First and foremost, this technology raises fears of government surveillance. Beyond all of the ethical concerns inherent in that topic, it is also important to urge caution in the application of facial recognition tools based on their current limitations as well as the propensity of AI systems to misclassify certain groups.

Taking this topic a few shades of grey further, the analytics company Faception claims to have developed a computer vision/machine learning tool to provide personality prediction analytics. They hope to see it applied to be able to identify terrorists or other criminals, however there are many ethical issues and potential misuses inherent in this model.

Decision Making:  The implication of the term “data driven decision making” is that this process relies entirely on “neutral” data and is free from the biases that a human decision maker brings to the table. However, given the evidence that societal biases can be built into these algorithms, we need to be cautious not only with outsourcing decisions to computers but also with leaning heavily on the outputs of ML during the decision making process – particularly in fields that could have a major impact on the rights and freedoms of entire populations.

Creativity and Intellectual Property issues:  As the ability of AI to produce “new” material increases, new questions arise: Can an algorithm be credited as an “inventor”? Can it be said to be violating Intellectual Property Rights if it is trained off of others’ creations? These debates are likely to continue for quite some time.

While the above topics raise questions without definitive answers at this point in time, stay tuned for our next newsletter installment where we look at some more obviously nefarious uses of data science technologies.

 Until next time, Happy Coding

Ben’s Take

Greetings, once again, from the home office (i.e. my grown son’s bedroom – yes, those are bunk beds behind me when we’re video chatting).

So, what’s going on in the analytics staffing space? Of course a number of companies have paused or eliminated projects as the economy has slowed. This, in turn, has led to reductions in analytic staff, both contract and permanent. While no one knows for sure, my best guess is that analytics hiring will start to pick up again in the July – August timeframe. I suspect that companies will be reluctant to hire permanent employees as they emerge from lockdown so they’ll begin by adding contractors. However, by late in the year, the need for both permanent and contract analytics staff will be growing again.

When you start looking for analytics contractors, think of us. Our role is to help out when your other vendors aren’t providing the quality you need to complete your critical projects. Our clients comment that our folks are consistently stronger than those of our competitors, who are usually large, general-purpose contracting firms. Why? Because we started as an analytics consulting firm, not a staffing firm. Thus, we developed the technical skill to determine if a resource really knows their stuff and the experience to know whether we’d like that resource on our team. If we wouldn’t want them on our team, we won’t ask you to put them on yours.

We lay out our core beliefs on our about us page. Compare them to the services you receive today. I think you’ll notice the difference.

This Week in Golden Record

We continue chugging along with our Golden Record matching and deduplication technology and are on track for an end of June initial release. If you’re facing a need to identify and track records that match across databases and files, please do contact me at Benjamin.Taub@Dataspace.com. I’d love to discuss how we might help.

Until next time, thanks for reading!

-Ben

Suggestions?

What do you think? How can we make this newsletter more useful to you? What topics would you like to see more of? Want to contribute an article? Just want to catch up and chat?

I’d love to hear from you! Email me at benjamin.taub@dataspace.com.