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<v Narrator>Data sharing.</v>
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In this lesson, we're going to talk
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about data sharing and some of the agreements you might use.
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Now, one of the things I've mentioned earlier
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in this class is that you can outsource a service
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or an activity
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but you can't outsource the legal responsibility for it.
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Even if I give that job
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to somebody else to do for me, I'm still responsible for it.
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So, I can have somebody else do my bookkeeping
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but at the end of the year,
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the IRS is still going to come after me if it's done wrong.
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And so, these are the things you have to think about
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when you're dealing with data sharing
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because this kind of stuff can come back to bite you.
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Now we're going to talk about
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four specific types of agreements.
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We're going to talk about service level agreements or SLAs,
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interconnection security agreements or ISAs,
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non-disclosure agreements or NDAs,
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and data sharing and use agreements.
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Let's talk about each of these.
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Now, a service level agreement
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or an SLA is a contractual agreement.
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Setting out the detailed terms
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under which a service is being provided.
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So I might have an SLA
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between me and my ISP, my internet service provider.
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It says they're going to provide me X amount of storage space,
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X amount of bandwidth, X amount of uptime,
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and X amount of hours a day of support.
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That is all in contract, in writing
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that we have both signed and we both agreed to.
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Now, that means, I don't have to worry
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about hosting my website, right?
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Correct.
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But if the site gets hacked,
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guess who's still going to have to answer for it?
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Me, because I'm still responsible.
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My company is still responsible.
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We've outsourced the task of running the web server
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but we have not outsourced the responsibility.
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You can't give away that responsibility.
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The second one we're going to talk about
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is an interconnection security agreement or ISA.
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Now, an ISA is an agreement used by federal agencies.
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So, we're talking about the US government here
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to set out security risk awareness processes
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and commit the agency
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and suppliers to implementing security controls.
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Now, essentially,
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these are used when the federal government wants
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to allow a third-party to connect into their system.
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So, let's say, I got a big contract to take over
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all of the IT training for the federal government.
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They would want to connect
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into my web server to allow all their users access.
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We would have to have one of these
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interconnection security agreements
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and it might say
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that every three months, we have to do a vulnerability scan
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and give them a report.
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We have to have all patches done within 30 days.
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We have to have X, Y, and Z done,
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whatever those requirements are to make sure
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that our security requirements
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meet their level of agreement.
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That way, we're not just plugging bad networks
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into the federal government's network.
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That's what we're talking about with an ISA.
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Next, we have our third one, which is an NDA
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A non-disclosure agreement.
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This is a contract that sets forth the legal basis
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for protecting information assets between two parties.
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So, I'm making a new course, for instance,
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for another company.
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We have an NDA that says, I can't disclose
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what's in that course until it goes live and is published
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because they want to make sure that their competitors
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don't figure out what our table of contents
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is going to look like and build a competing course.
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That would be an NDA.
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We can't tell other people outside of the two
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of us what's going on.
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I have some other partners that I work with
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inside the business, and we have NDAs
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with those organizations as well.
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So, they can tell us things about future upcoming products
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they might be working on, but I can't tell you about it
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because you're not part of that NDA.
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Only the two of us are.
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And so we have this, basically it says,
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I'm going to keep your secrets and you're going to keep mine
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and neither of us will tell other people.
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That's what an NDA does.
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And then we have data sharing and use agreements.
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Now, these are an agreement that sets forth the terms
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under which personal data can be shared or used.
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So, let's say, you bought this course
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on some kind of a platform, and in part
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of their privacy policy, it says, they can monitor your use
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of the course, and they can use that to then sell that
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to third parties to tell them
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about e-learners in the market.
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They can then say, "Well, out of all the students,
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we have 50% finish all of their courses,
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20% by a second course.
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70% take courses in English.
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Whatever those facts and figures are,
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I'm just making that up.
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But they can share that data with a third-party
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if they have permission when they collected it from you
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and they now have a data sharing agreement in place.
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This is the idea of data sharing agreements.
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I can take my corporate data that I've collected off
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of those people that are using my service and then share it
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with somebody else under the terms of that agreement.
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Now, all of these things predicate themselves
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on us having personal data on our users
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and this becomes a large data set for us.
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Now, these data sets may be subject to pseudonymization
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or de-identification to remove personal data.
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Now, we've talked a lot about privacy inside this course
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and one of the ideas here
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is that we can actually take your data
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and we can de-identify you from it.
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And that makes that data no longer personal data.
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It just becomes big data.
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And this is done a lot by a lot of different companies,
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the Googles and the Facebooks and others of the world.
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Even if they don't have permission, to have
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your personal data, because you have opted out,
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there might be information about you
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at large that could be used if they de-identify you.
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And what this means is we want to take out anything
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that can identify you uniquely.
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So, let's say, I'm an online training company
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and I have lots of students in my site
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but I never asked you if I could share your personal data.
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Well, that means, I can't share your personal data
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but I can de-identify you and then use that data.
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And what I mean by this is I could say,
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out of the 100,000 students who took this course,
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99% passed on their first try.
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Now that doesn't identify you
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as one of my students in any way.
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It doesn't identify you in the least.
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You are just one of those 100,000.
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So, that is now de-identified.
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Or I can take smaller groups of information from my course.
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For instance, I could say males who are 35 to 40 years old
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pass at a rate of 80% or higher.
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Females who are 18 to 24 pass at 99%.
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And again, I'm just making up numbers.
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This doesn't, these aren't real numbers
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but it gives you the idea of how we can take subsets
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of the larger data and it doesn't identify you uniquely.
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This is the idea
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of de-identification or pseudonymization,
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by taking away those personal details and making it
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about the larger group instead of an individual.
