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Legal Technology

Practice Innovations: Will the Internet of Behavior change how we act and interact?

Don Philmlee  Technology Strategist

Don Philmlee  Technology Strategist

As we evolve toward the Internet of Behavior, will people be able to accept being monitored, tracked, and analyzed with a mix of data technology and behavioral science?

In 2008, the number of objects connected to the internet exceeded the number of people on the planet — now, more than a dozen years later, there are more than 50 billion internet-connected devices.

This mass of connected objects, often called the Internet of Things (IoT), has slowly invaded our homes and workplace and now includes such items as smart lightbulbs, children’s toys, smart thermostats, web cameras, and more. However, the IoT is rapidly transforming, and increasingly these smart devices are being used to track, change, or monitor human behavior.

This new technology is called the Internet of Behavior (IoB), and it is monitoring, tracking, and analyzing our everyday actions and biology. Think of the IoB as a combination of technology and data mixed with behavioral science that tries to make sense of human behavior.

It works like this: Passive devices, such as a smartwatch, can track our health metrics and then give advice or send a reminder to us on how to improve our health. But the IoB is moving past just providing this passive advice and into more proactive and intrusive interactions. For example, during the COVID-19 pandemic, organizations used the IoB to monitor compliance with corporate health protocols, including actions like hand washing, face mask compliance, or social distancing. A computer then directly warns a person if they violate the health protocol.

Collecting data & analyzing behavior

The IoB can take collected user data and use behavioral psychology to analyze it, which in turn could influence how organizations interact with people. The IoB can collect and process user data from different sources such as social media, location-tracking information, client information, data provided by government agencies, and more. By connecting this digital detritus from how we live our lives to behavioral science, an organization can more easily predict and influence our behavior. Ideally, this analysis can show an organization how to market its products or services in more appealing ways to customers.

The IoB is not just for analyzing users based on online behavior, however. It could allow corporations or governments to analyze user interactions with devices such as computers, smartphones, smart speakers, smart cars, car cameras, and more. Organizations would then be able to build a profile on a user using a lot more than their online profile from Twitter or Instagram.

Unlike user data collection that is voluntary, the IoB does not depend on information that the user willingly provides. This has enormous potential but also raises cybersecurity concerns, user privacy issues, and understandable apprehensions that Big Brother is watching.

Tech research and consulting firm Gartner stated it believes, however, that the IoB is an important technology trend as it can not only capture how people behave but can also analyze, understand, and respond to that behavior. IoB can then use machine learning algorithms to predict and detect which psychological variables can be used to elicit a specific outcome. The IoB can provide an organization with new ways to market and target sales of their products and services or influence user behavior. While the IoB can be used to influence choice, idealistically, it could also be used to help improve efficiency and people’s quality of life.

Not surprisingly, however, the IoB does raise some ethical, social, and security-related concerns:

      • No clear rules for data privacy — Who owns a users’ data? Who governs how this data is kept private? What about aggregated and analyzed user data? Does that belong to the organization? What happens if these user datasets are sold or shared?
      • Ethical issues — Is it ethical to collect users’ data and actions and then use this data to influence their behavior?
      • Data accuracy — How is data gathered and used, particularly at such large scales? The IoB is only as good at the data it has been fed; and with so much data coming in, is it reasonable to consider how that data is collected and whether it honestly and accurately reflects the user?
      • Higher value targets — As user data gets more detailed, it becomes a more lucrative target for theft by cyber-criminals going after an organization’s data.
      • Targeted and effective phishing — As IoB encompasses more users, those users will be increasingly targeted by scammers through phishing attempts. Scammers can take highly detailed IoB data and develop highly sophisticated and more effective phishing attacks.
      • Limited security — Often, most internet-connected devices used to collect user data have limited security protections with simple passwords and are not frequently patched and updated. This makes them a weak link for cyber-attacks that put an organization’s IoB efforts and users’ data at constant risk.
      • Behavioral analysis is not 100% accurate — Behavior analysis can only show so much, and it may fall short of providing a true understanding of the meaning and context of a person’s life and online actions.
      • Difficult user opt-out — Today, a user can opt-out of an organization’s data collection effort. What happens when that data is more deeply embedded in complex aggregated datasets? Is it possible to opt-out?
      • Loss of trust — While it may be legal to collect and analyze user data, will users see the influencing of their behavior as creepy, intrusive, and going too far? How will this impact public perception of the organization?
      • The user must get real value — If a user wants to share some data with one organization, can that information be shared? For example, an automobile driver may want to share their speed and location with their insurance company to get lower rates. However, the same driver may object to sharing the same information with law enforcement. If a user surrenders their data to the IoB, they must get tangible benefits in return, or they will reject participation.

The IoB may still be in its infancy, but it is growing quickly as organizations embrace this new technology. Gartner estimates that by 2023 more than 40% of the global population will be tracked by IoB in order to influence behavior. That means it is likely that IoB will soon become part of the background noise of how business is conducted on the internet.

Without a doubt, the IoB confers some substantial advantages, but organizations that do choose to use IoB must work to secure increasingly sensitive data about users. It is also critical for governments to set clear boundaries on how the IoB is used and how user privacy can be protected. Given how fast the technology is growing, data protection laws will undoubtedly struggle to keep pace.

On a positive note, if the IoB is used effectively, it could potentially lead to a better understanding and anticipation of what a user needs or what a client wants. It has the potential to provide a more enhanced and effective channel of communications between organizations and their users or clients.