Case Study: Targeted Ads

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Data Science Ethics

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University of Michigan

Data Science Ethics

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What are the ethical considerations regarding the privacy and control of consumer information and big data, especially in the aftermath of recent large-scale data breaches? This course provides a framework to analyze these concerns as you examine the ethical and privacy implications of collecting and managing big data. Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency as you gain a deeper understanding of the importance of a shared set of ethical values. You will examine the need for voluntary disclosure when leveraging metadata to inform basic algorithms and/or complex artificial intelligence systems while also learning best practices for responsible data management, understanding the significance of the Fair Information Practices Principles Act and the laws concerning the "right to be forgotten." This course will help you answer questions such as who owns data, how do we value privacy, how to receive informed consent and what it means to be fair. Data scientists and anyone beginning to use or expand their use of data will benefit from this course. No particular previous knowledge needed.

À partir de la leçon

Privacy

Privacy is a basic human need. Privacy means the ability to control information about yourself, not necessarily the ability to hide things. We have seen the rise different value systems with regards to privacy. Kids today are more likely to share personal information on social media, for example. So while values are changing, this doesn’t remove the fundamental need to be able to control personal information. In this module we'll examine the relationship between the services we are provided and the data we provide in exchange: for example, the location for a cell phone. We'll also compare and contrast "data" against "metadata".

History of Privacy15:37

Degrees of Privacy10:27

Modern Privacy Risks12:16

Case Study: Targeted Ads3:15

Case Study: The Naked Mile2:43

Case Study: Sneaky Mobile Apps5:13

Rencontrer les enseignants

H.V. Jagadish
Bernard A Galler Collegiate Professor
Electrical Engineering and Computer Science

[MUSIC]

Often, when you look for something on the web, you will find ads for

that thing, say a pair of shoes, for days after you look for it.

This can be annoying.

The question is, what's our view of

this sort of behavior in terms of a social consensus?

What's ethical, what's not ethical?

Let's take a step back and see why this is happening.

The likelihood that you'll be interested in buying a pair of shoes,

today, is not that great.

I'm just going to make up a number.

Let's say that there's a 1 in 1,000 chance that you might be

persuaded to buy a pair of shoes if you're just a random person.

On the other hand, if you looked at a pair of shoes,

even if you decided not to buy it today.

Even if you decided that was not interesting.

You've indicated that at least you're open to the possibility of buying a pair

of shoes.

And this considerably increases the odds that you could be persuaded to buy a pair.

Lets say it's now a 1 in 10 chance.

Well, that's a huge improvement in odds, as far as a potential seller is concerned.

Obviously, advertisers now want to take that into account and try to show

you different options in shoes and see if there's something that catches your fancy.

The problem is, if this is overdone, this gets annoying.

In the real world, we have centuries of experience to calibrate

this kind of interpersonal behavior.

If you express interest in a store, you should expect a salesperson to

suggest some options, suggest some alternatives that are similar, and so on.

But once you've clearly indicated that you're not interested,

you're not going to have the salesperson repeatedly pestering you over and

over with the same or alternative shoes.

It's this, knowing when to stop, that we understand how to do in real,

personal interaction and that we don't yet have good enough signals for on the web.

The consequence of which is that people feel kind of irritated and pestered.

At this point, my sense is that there is some irritation.

This is something that we probably will, over the years,

develop better technology for.

Companies are motivated not to annoy potential customers,

and so they'll figure things out.

And we will end up with some sense of consensus around good business practices

where some amount of targeted advertising is considered good and acceptable.

And, beyond some line, we will say it's too much and it shouldn't happen.

Up to this point, we don't have that line defined, and

so we're all targets for advertising related to things that we've looked for

[MUSIC]

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