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Part 3: Questions for your vendor

 
If you are considering the utilization of intelligent machines in your HR/Operations processes, here are some questions you might consider.

  1.  Tell me about your views on product liability
    Be sure to have a long conversation about how the tool works and how the vendor is monitoring the impact of machine learning curves. You’ll learn a lot by raising the topic of product liability. Most vendors still imagine that we are in the first generation of software where liability is not really a possibility. The key question here is ‘what if your tools recommendations cause damage to our people or our business?
  2. How do we make changes to the historical data?
    Most machine learning systems are ‘black boxes’. If you ask the designers how they work, they can only explain about 80%. That means that you are likely to want to modify the results that the machine produces. It is likely that the answer to this question is ‘you can’t.’ Having the conversation is what’s important. It will give you a window on your real risks.
  3. What happens when we turn the “it” off? How much notice will we receive if you turn it off?
    Imagine that you are using a tool that does the job of several employees (sourcers who review resumes, for example). If the tool fails in a way that requires a shutdown, what sort of advance warning do you get. Since most providers are in experimental stages, the answer to this question also matters if the project ceases to operate. In a very real way, these are digital employees and it is best to have a replacement plan.
  4. Do we own what the machine learned from us? How do we take that data with us?
    Part of the way that these systems operate is that they learn in both the aggregate and individual case. Most vendors guarantee that your data is ‘anonymized’. You still may not wish to have your operating practices be a part of some larger benchmarking process after you change suppliers. Being very clear about whether the system will retain evidence of your participation after you go is of strategic import.
  5. What are the startup costs, resources and supervision?
    We know precious little about the behavior of intelligent machines. There is good reason to expect that their impact on your resource consumption is greater than anyone thinks today. Like any employee, they require training, supervision and discipline. Make sure you have a very clear picture of the Total Cost of Ownership of any leaning machine you enable.

The age of human-machine integration is in its infancy. It is inevitable. In the transition, it is important that we move forward carefully with a clear picture of the risks and ethical issues. This note is a starting point.

Next: Managing your algorithm.

Read the three-part series:

  1. Part 1 of 4: Liability – June 27, 2017
  2. Part 2 of 4: Basic Ethics Questions – June 28, 2017
  3. Part 3 of 4: Questions for your vendor – June 29, 2017
  4. Part 4 of 4: Managing Your Algorithm – July 02, 2017

(This series is the direct outgrowth of a presentation that I did with
Stacey Harris from Sierra Cedar.)



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