Chapter 4 – The Ethical Challenges of Online Behavioral Targeting (OBT)

Below: Mark Zuckerberg, CEO of Meta, predicts how AI will be used to hyper-personalize OBT:

“The one opportunity that we just usually talk about… is just the ability to make it so that advertisers are increasingly just going to be able to give us a business objective… and have the AI system basically figure out everything else that’s necessary, including generating video or different types of creative that might resonate with different people that are personalized in different ways, finding who the right customers are. All of the capabilities that we’re building, I think, go towards improving all of these different things. So I’m quite optimistic about that.” – Meta Platforms, Inc. (META) Third Quarter 2025 Results Conference Call, October 29th, 2025

Below: An example of the ways in which Online Behavioral Targeting (OBT) affects the character of content that appears in a user’s app feed. What does the IRCTC official’s response to the user suggest about the user’s browsing habits?

Overview

In the prior chapter, we explored the benefits and risks associated with a personalized Internet experience from the user’s perspective. In this chapter, we turn the tables and look at OBT from the ethical perspective of the business owners who use them.

This week’s discussion will place you in a position of a business owner whose success depends on remaining competitive. The focus is on a marketing strategy that will enable the business to place their ads in front of users according to a set of ethical principals. In this week’s discussion, you will have the decision-making power to employ an algorithm that predicts the characteristics and behaviors of your customers so that you can gain a competitive advantage. How far would you go, given the opportunity to calculate some very intimate details about them?

Below is a simple clickable diagram that illustrates how metadata is used in generating marketing leads for predictive algorithms.

Key Terms

General Data Protection Regulation (GDPR) and ePrivacy Directive (ePR): These are two regulatory statutes that describe compliance requirements for data privacy for all websites or systems that are accessible in the UK and EU, respectively. Both regulations pertain to, among other things, the permissible collection and use of cookie data. Cookiebot is a service that helps websites to operate in compliance of these regulations. Below is an example of the user-facing interface for managing the use of cookies on a website that uses the Cookiebot tools.

Mobile Advertising ID (MAID): Every mobile device (smartphone or tablet) contains a unique identifier that is used by advertising services to target a specific device. When the apps on your phone capture your metadata, it associates it with your MAID. How to Find the Mobile Ad ID on Apple and Android Devices. The MAID can be used for unethical purposes, as described in the latter articles below.

Open-source intelligence (OSINT): (Excerpted from the Wikipedia entry). Huge collections of data about individuals can be obtained through open-source resources provided the information does not require any type of clandestine collection techniques to obtain it and that it must be obtained through means that entirely meet the copyright and commercial requirements of the vendors were applicable. These open sources include:

• Media: print newspapers, magazines, radio, and television from across and between countries.
• Internet, online publications, blogs, discussion groups, citizen media (i.e. – cell phone videos, and user created content), YouTube, and other social media websites (i.e. – Facebook, Twitter, Instagram, etc.). This source also outpaces a variety of other sources due to its timeliness and ease of access.
• Public Government Data, public government reports, budgets, hearings, telephone directories, press conferences, websites, and speeches. Although this source comes from an official source they are publicly accessible and may be used openly and freely.
• Professional and Academic Publications, information acquired from journals, conferences, symposia, academic papers, dissertations, and theses.
  Commercial Data, commercial imagery, financial and industrial assessments, and databases.
  Grey literature, technical reports, preprints, patents, working papers, business documents, unpublished works, and newsletters.

An example of an app that draws from OSINT data is the Predictim app whose service evaluates whether the babysitter you intended to hire poses any risks. (See the optional article resource below from CBS News).

What should you be focusing on?

Your objective in this module is:

• Develop a strategic position on the use of OBT from a business person’s perspective which takes into account its ethical ramifications.

Readings & Media

   Required     Interaction: What information is being tracked while you interact online? (15:00)

Spend a few minutes clicking around ClickClickClick.click to see just how much metadata can be collected about your Web browser behavior as you navigate online. This will give you a sense of how sophisticated Web browser tracking technology has become. In addition, consider that the manner of your interaction can be tracked to identify patterns of your engagement that are as unique as your fingerprint or manner of walking.

    Required     Interaction: What is the fingerprint of your browser? (15:00)

Go to the Electronic Frontier Foundation’s dedicated webpage for checking your browser’s fingerprint. After checking your browser, skim through their page, “How Do trackers Work?”

    Required     Video: “Why is your phone SECRETLY connecting to these sites to TRACK you?” by Liron Segev via YouTube (15:37).

This video publisher produces investigative content related to computer systems, hacking, privacy, and many other popular issues related to common user experiences. The style of his presentation is intended for entertainment purposes, so it is not presented in a scholarly manner. However, his live demonstrations are revealing and informative.

In this video, Liron Segev installs Pi-Hole, a diagnostic app that tracks all of the Internet locations that his phone connects to and investigates the ones that appear to be sharing data.

    Required     Article: “Facebook to stop targeting ads at UK woman after legal fight” Published March 22, 2025 by the BBC. (2 pages)

This article describes the legal argument of employing OBT through metadata capture versus the business’s right not to give away their services for free.

    Required     Database: “FTC Sues Kochava for Selling Data that Tracks People at Reproductive Health Clinics, Places of Worship, and Other Sensitive Locations” Published August 29, 2022 by the Federal Trade Commission. (3 pages)

This article details the case against Kochava Inc., a data broker service, for selling metadata that can “…reveal people’s visits to reproductive health clinics, places of worship, homeless and domestic violence shelters, and addiction recovery facilities.” This statement is a bit misleading. As you will see when you read the entire article, the data referred to here comes from mobile devices – not from actual people.

However, it is possible (at great expense) to employ a service that will convert the Mobile Advertising ID (MAID) of a smartphone or tablet to a known person: Inside the Industry That Unmasks People at Scale. There is another tool, Locate X, that (also at great expense) can track the movements of people based on their smartphone or tablet location and display their journey on a map: Inside the U.S. Government-Bought Tool That Can Track Phones at Abortion Clinics. There are ramifications for this capability, such as a state government’s law enforcement agency using these tools to prosecute a woman (and whoever is transporting her) who crosses state lines to obtain an abortion when it is illegal her home state – all without a warrant. In the wrong hands, Locate X can track people attending certain houses of worship, jurors, judges, prosecutors, and teachers.

    Required     Article: The ethical codes of using OBT (17 pages)

Review “The Ethics of Legal and Ethical Challenges of Online Behavioral Targeting in Advertising“. You only need to review the parts about the ethical codes related to OBT. You are free to skim the other parts related to all of the methods of data collection if it would help you with your project. The main focus of this piece begins on page 18 within the PDF under the heading “Ethical Analysis of Online Behavioral Targeting and the FTC Principles and Guidelines”

    Required     Article: The case for banning OBT (5 pages)

Review The New Republic – “Ban Targeted Advertising.” David Dayan makes the case for banning targeted advertising altogether. He suggests that not only does the “surveillance economy” fail to deliver anything meaningful to advertisers but he believes building massive databases of metadata creates an attractive target for hackers. The risks outweigh the perceived benefits.

Dayan argues from both a business perspective and from an ethical perspective. As you read, consider whether Dayan’s commentary is a strong argument for banning OBT, or whether his argument would be weaker if the OBT system had a few tweaks.

Optional: Supplemental resources related to OBT and publicly obtained data

Marketoonist – The personalization privacy paradox: This brief article describes and illustrates “Zero party data,” a category of user data that is intended to be different than the third-party metadata described above in OBT. If you are furthering your studies in Marketing, this might be a trend to follow.

Privacy Badger is a browser extension that blocks trackers. Review what it claims to remediate.

The Federal Deposit Insurance Corporation (FDIC) Center for Financial Research describes how metadata from one’s digital footprint is being used as a basis of determining credit worthiness. “On the Rise of the FinTechs—Credit Scoring Using Digital Footprints” includes the following statements:

The growth of the internet leaves a trace of simple, easily accessible information about almost every individual worldwide – a trace that we label “digital footprint”. Even without writing text about oneself, uploading financial information, or providing friendship or social network data, the simple act of accessing or registering on a webpage leaves valuable information. As a simple example, every website can effortlessly track whether a customer is using an iOS or an Android device; or track whether a customer comes to the website via a search engine or a click on a paid ad. In this project, we seek to understand whether the digital footprint helps augment information traditionally considered to be important for default prediction and whether it can be used for the prediction of consumer payment behavior and defaults.

…Using more than 250,000 observations, we show that even simple, easily accessible variables from the digital footprint equal or exceed the information content of credit bureau scores. Furthermore, the discriminatory power for unscorable customers is very similar to that of scorable customers. Our results have potentially wide implications for financial intermediaries’ business models, for access to credit for the unbanked, and for the behavior of consumers, firms, and regulators in the digital sphere.

BBC News: “Bereaved mother criticises Facebook over baby ads.” This article describes how a woman who suffered the loss of a stillborn birth continued to receive targeted ads for baby products and related content no matter how often she objected to the ad placements through Facebook’s feedback mechanisms. This article will give you a sense of how, despite the incredible capabilities of OBT, it is not “intelligent” enough to know when circumstances in a person’s life have changed.

CBS News: “AI babysitting service Predictim vows to stay online after being blocked by Facebook and Twitter.” Find out why Predictim, an app designed to evaluate the risk of the babysitter you intended to hire (which sounds like a good idea), turned into a problem so unmanageable that the service was suspended. This is relevant in this chapter because it is predicated on the ability of the system to “scrape” social media content about an applicant.

The World Privacy Forum is a research organization on the forefront of examining privacy issues in the digital era.