There have been many names for the IoT over time: ubiquitous computing, ambient intelligence, machine-tomachine communications, pervasive computing, and, most recently, cyberphysical systems. The terms emerged from various disciplines, but they all point in the same direction. These persistent attempts to find a suitable term for the phenomenon reveal an awareness that the world is in rapid transition towards more comprehensive monitoring and connectivity, that this will likely have a profound impact on our lives, and that it is important to start anticipating the potential consequences. Our physical and informational world is evolving, and with it, the concept of privacy as we know it.The authors argue that
The IoT will expand the data collection practices of the online world to the offline world.
— The IoT will enable and normalize preference and behavior tracking in the offline world. This is a significant qualitative shift, and a key reason to evaluate these technologies for their social impact and effect on historical methods of privacy preservation. The very notion of an offline world may begin to decline.
The IoT portends a diminishment of private spaces.
— The scale and proximity of sensors being introduced will make it harder to find reserve and solitude. The IoT will make it easier to identify people in public and private spaces.
The IoT will encroach upon emotional and bodily privacy.
— The proximity of IoT technologies will allow third parties to collect our emotional states over long periods of time. Our emotional and inner life will become more transparent to data collecting organizations.
Given the likelihood of ubiquitous data collection throughout the human environment, the notion of privacy invasion may decompose; more so as people’s expectation of being monitored increases.
— Much of consumer IoT is predicated on inviting these devices into our lives. The ability to know who is observing us in our private spaces may cease to exist. The IoT will hasten the disintegration of the ‘reasonable expectation of privacy’ standard as people become more generally aware of smart devices in their environments.
When IoT devices fade into the background or look like familiar things, we can be duped by them, and lulled into revealing more information than we might otherwise. Connected devices are designed to be unobtrusive, so people can forget that there are monitoring devices in their environment.
IoT devices challenge, cross and destabilize boundaries, as well as people’s ability to manage them.
— The home is in danger of becoming a ‘glass house,’ transparent to the makers of smart home products. And, IoT devices blur regulatory boundaries – sectoral privacy governance becomes muddled as a result.
As more and more products are released with IoT-like features, there will be an “erosion of choice” for consumers – less of an ability to not have Things in their environment monitor them. Market shifts towards ‘smart’ features that are intentionally unobtrusive lead to less understanding of data collection, and less ability to decline those features.
The IoT retrenches the surveillance society, further commodifies people, and exposes them to manipulation.
The IoT makes gaining meaningful consent more difficult. The IoT is in tension with the principle of Transparency.
The IoT threatens the Participation rights embedded in the US Fair Information Practice Principles and the EU General Data Protection Regulation.
IoT devices are not neutral; they are constructed with a commercial logic encouraging us to share. The IoT embraces and extends the logic of social media – intentional disclosure, social participation, and continued investment in interaction.
The IoT will have an impact on children, and therefore give parents additional privacy management duties.
The report identifies 'emerging frameworks and strategies' regarding IoT privacy— Children today will become adults in a world where ubiquitous monitoring by an unknown number of parties will be business as usual.
Having broad non-specialist social conversations about data (use, collection, effects, socioeconomic dimensions) is essential to help the populace understand the technological changes around them. Privacy norms must evolve alongside connected devices – discussion is essential for this.
Human-Computer Interaction (HCI) and Identity Management (IDM) are two of the most promising fields for privacy strategies for IoT.
A useful design strategy is the ‘least surprise principle’ – don’t surprise users with data collection and use practices. Analyze the informational norms of personal data collection, use and sharing in given contexts.
Give people the ability to do fine-grained selective sharing of the data collected by IoT devices.
Three major headings for emerging frameworks and strategies to address IoT privacy:
— User Control and Management
User Control and Management Strategies
• Data Minimization – only collect data for current, needed uses; do not collect for future as-yet-unknown uses
• Build in Do Not Collect ‘Switches’ (e.g., mute buttons or software toggles)
• Build in wake words and manual activation for data collection, versus the truly always-on
• Perform Privacy Impact Assessments to holistically understand what your company is collecting and what would happen if there was a breach
• Make it easy for people to delete their data
• Make it easy to withdraw consent
• Encrypt everything to the maximum degree possible
• IoT data should not be published on social media or indexed by search engines by default – users must review and decide before publishing
• Raw data should exist for the shortest time possible
— Identity Management
• Design strategies: > Unlinkability – build systems that can sever the links between users’ Emerging Frameworks and Strategies to address activities on different devices or apps >; Unobservability – build or use intermediary systems that are blind to user activity
• Give people the option for pseudonymous or anonymous guest use
• Design systems that reflect the sensitivity of being able to identify people
• Use selective sharing as a design principle > Design for fine-grained control of data use and sharing > Make it easy to “Share with this person but not that person”
• Create dashboards for users to see, understand and control the data that’s been collected about them
• Design easy ways to separate different people’s use of devices from one another
— Notification Strategies
• Timing has an impact on privacy notice effectiveness.
• Emerging privacy notice types: > Just-in-time; > Periodic; > Context-dependent; > Layered
• Test people’s comprehension of privacy policies
• Researchers are exploring privacy notification automation: > Automated learning and setting of privacy preferences; > Nudges to encourage users to think about their privacy settings; > IoT devices advertising their presence when users enter a space
— Governance Strategies
• Creation of baseline, omnibus privacy laws for US
• Regulations restricting IoT data from certain uses
• Requirement to test privacy policies for user comprehension
• Expansion of “personally-identifiable information” to include sensor data in the US
• Policymaker discussions of the collapse of the ‘reasonable expectation of privacy’ standard
• Greater use of the ‘precautionary principle’ in IoT privacy regulation
• More technologists embedded with policymakers
• Trusted IoT labels and certification schemes