Learners consider the features of a “Smart Home” and explore a worst-case scenario, namely, that a smart home might be used in a gaslighting attack. Gaslighting is a term, first introduced in 1969 by British psychiatrists, to refer to situations where one person seeks to induce mental illness in another person by subtle and subversive changes to the target’s environment — for example, the lighting in one’s home. Learners are positioned to design policy and technical solutions.
Please Note: This scenario contains potentially distressing content related to domestic abuse.
The “Internet of Things” is poised to shape societies for years to come. The vision is for physical objects, of all kinds in all places, to dynamically and intelligently respond to human needs and circumstances. Manufacturers and tech optimists promise more efficiency and happiness. The New York Times puts it this way:
Cars, door locks, contact lenses, clothes, toasters, refrigerators, industrial robots, fish tanks, sex toys, light bulbs, toothbrushes, motorcycle helmets — these and other everyday objects are all on the menu for getting “smart.” Hundreds of small start-ups are taking part in this trend — known by the marketing catchphrase “the internet of things” — but like everything else in tech, the movement is led by giants, among them Amazon, Apple and Samsung.
The constellation of technologies that make up the Internet of Things will, in all likelihood, create benefits and lead to new social and economic opportunities. On the other hand, just as likely, the Internet of Things will also enable inappropriate or unsafe behaviors, create challenges and unintended consequences, and lead to harms.
According to Melvin Kranzberg, a philosopher of technology, any “technology is neither good nor bad; nor is it neutral.” Accordingly, the Internet of Things will surely be empowering and problematic at the same time, a double-edged sword. How empowering? How problematic? And, for whom? While somewhat difficult to predict, the social and economic impacts of this foundational technology, experienced directly and as ripple effects, are likely to be very substantial. At least the following values are at stake: privacy, security, control, and freedom.
Leading technologists, Francine Berman and Vinton Cerf, write: “The difference between an IoT [Internet of Things] that enhances society and one that diminishes it will be determined by our ability to create an effective model for IoT governance” (Berman & Cerf, 2017). One approach for discovering what a model of governance needs to address is to explore worse-case scenarios—that is, what might go wrong and what might be done so that big problems are less likely to occur.
Stepping back, the Internet of Things can be viewed as a network of objects and devices that sense, compute, exchange information, and respond. With some engineering, anything that has an on-off switch might plausibly become part of the Internet of Things. By 2020, it is expected that more than 30 billion things will be connected to the Internet. More impressive still, the Internet of Things is a unifying technology because a smart object might be located anywhere: in cyberspace, in the built environment, and in biological systems. Even ordinary things such as paint, food, and, indeed, any material, might be made smart in the future.
The “Smart City,” for example, refers to a vision of greater efficiency, safety, and less environmental impact. Sensors embedded in roads might monitor traffic volumes and dynamically adjust highway tolls, optimizing traffic flows, based on the willingness of people to pay for fast travel times. Safety cameras, mounted on traffic lights, might be used to enforce the rules of the road. Automatic license plate readers might identify drivers, or at least cars, who are speeding or running red lights. On-board sensors in buses might monitor locations and expected arrival times at bus stops and send updates to mobile phones. This technology, however, might collect and store data on the movement of people which, in turn, might be useful for identifying welfare fraud and other crimes. In so doing it might also violate individual privacy. In the Smart City many different data streams might be brought together to offer an overall model of the city and reveal patterns of where groups and individuals go.
The “Smart Store,” such as Amazon Go, eliminates check-out lines. Enter the store, identify yourself by scanning a mobile phone at a turnstile, shop as you normally would, and just leave the store—there you go: no lines, a more efficient shopping experience, and individual empowerment. Perhaps facial recognition technology or ID chips embedded in customers’ bodies will do away with the need to explicitly authenticate with a phone. It has been reported that Amazon is going to open 3,000 such stores by 2021, targeting neighborhoods of affluent, young urbanites. People with low incomes, those who decide against owning a mobile phone, or those who object to using a phone to authenticate in public spaces, are unlikely to use Smart Stores. Similarly, cars might be equipped with communication capabilities for purchasing products and services. While out and about, order your favorite coffee drink, pick it up at the nearest drive-thru, and use your shopping cart to pay for it—easier, more efficient transactions, and perhaps more control on how one’s time is spent.
The “Smart Home” promises greater control, efficiency, and safety, for new and better human experiences at home. In the Smart Home, lightbulbs, doorbells, furnaces, lights, air conditioners, coffee pots, and locks will be controlled from a mobile phone. Offering pleasure and efficiency, smart speakers, which translate the human voice and language into commands for the Internet of Things, might become the control center of homes. But, such speakers, unbeknownst to people at home, might also be able to identify highly personal things such as indicators of mental illness. Toys and vacuum cleaners, connected to the Internet, might respond to human commands and home conditions. Hidden cameras, sometimes called “nanny cams,” might be used to monitor the front door or the baby’s room. Other home cameras, installed in the living room and kitchen, might be used by adult children to keep in touch with their elderly parents. Sensors in the floors might identify when an elder falls or whether their balance is deteriorating or improving after, for example, a hip replacement. The same sensors might also learn to identify people by their gait and detect familiar and first-time visitors. Smart meters measuring electricity and water consumption might enable homeowners to save money and reduce their home’s environmental impact. However, should a third-party gain access to time-series data of electricity and water consumption a good deal might be inferable, for example, television watching, cooking, and showering habits.
The “Smart Body,” might contain sensors that measure vital indicators of health, enabling people to set goals, measure progress, and keep medical personnel appraised. Such data might restructure the doctor-patient relationship and make it more patient-centered. With granular analysis of sensor data in combination with atmospheric data—temperature, pollen counts, measures of particulate concentrations—new discoveries in health care might be made. At the same time, life insurance companies might use this data to dynamically adjust their rates. In a different vein, police departments might use data about individuals—their location, sleeping patterns, and physiological measures—to help solve crimes.
The Internet of Things on a “Smart Farm” might signal such information as: it’s time to irrigate the corn (because a sensor indicates that the soil is dry), it rained 5 mm yesterday, a predator threatens the herd of cattle (because the heard is sending a collective signal of anxiety), the feed stock is low, the cold storage room is up to 3 Celsius, someone is in the barn, the gate was left open.
In wild places, the “Smart Ecosystem,” might be designed to include sensors and cameras, strategically placed in the woods, for investigating the movements of wildlife. When chips are embedded in wolves and livestock, for example, wildlife managers might monitor their travels and, like a video game, zap them with an electric shock to keep them separated. Perhaps, via their mobile phones, hikers will be informed of the presence of a nearby grizzly bear. But, what of hunters: Should they be informed? Might hunters pretend to be hikers? Not plausible? Perhaps. But, with the Internet of things, if it can be imagined, it might be possible.
As these examples show, the opportunities to deploy the Internet of Things appear to be boundless, limited only by our technical imagination for new human experiences. Yet, in these examples, we can also discern the double-edged sword of this technology, where features and capabilities might produce benefits, along with harms and potentially distressing consequences.
One stunning example of a harm occurred on October 21, 2016 when the Internet of Things was exploited to execute a distributed denial of service attack, the so-called “2016 Dyn cyberattack.” It is believed that the attackers constructed a botnet by infecting residential printers, cameras, baby monitors, and so forth with malware. That malware was used to flood an Internet domain name service with so many requests that legitimate requests could not be served, leading to major websites being unavailable. The root cause of the attack was poor security of ordinary residential objects that were connected to the Internet. In another example, in May 25, 2018 the FBI issued a public service announcement, requesting all owners of small office and home routers to reboot them. Bad actors had introduced malware that could be used to exploit routers and to capture information and render them inoperative.
Envision a smart home filled with Internet-connected objects that can be used to monitor and control the home. Furthermore, imagine that Cory and Riley, once married, have separated, because of Cory’s controlling and abusive behavior.
Riley continues to live in the home they once shared.
Cory set-up the Internet of Things at home, knows the passwords, and has deep knowledge for the home network and connected devices. Riley, however, has limited knowledge for how the technology is set-up.
Cory has started to treat Riley cruelly by utilizing the features of their Smart Home. Cory can flicker the lights, adjust the thermostat, ring the doorbell when no one is there, and other manipulations to Riley’s home environment.
Seeking to psychological harm someone by controlling an environment through subtle, often creative and subversive, forms of manipulation is sometimes called “gaslighting.” The goal of the abuser is to make the victim question his or her memory, perception, and understanding. First described by British psychiatrists in 1969, the term gaslighting comes from a stage play, Gaslight, where a husband surreptitiously manipulates small elements at home, including the gas lamps, seeking to convince his wife that she is insane.
In modern days, Cory is using Internet of Things technology in the home to gaslight Riley, making Riley feel unsafe and unsure about what is real.
Consider the Internet of Things in the context of an affluent home, that is, a home where its occupants have sufficient discretionary income to purchase the latest Internet-ready devices. Take a worse-case scenario perspective and investigate how the home might be used as a tool for gaslighting. How might attempts for control and psychological manipulation be resisted or prevented?
To engage the design prompt, follow this suggested process:
- Explore technical features. Explore the technical features of the home. What devices are connected to the Internet? How are they controlled and interconnected? How might the home’s devices send subtle and not so subtle signals into the living spaces? To capture and represent your ideas, draw a sketch that presents the devices and their physical and digital interconnections.
- Write a value scenario. Write a 200-word value scenario in which Cory employs features of their smart home in a gaslighting attack, that is, to try to psychologically manipulate Riley. How might Riley be an indirect stakeholder? How is Cory a direct stakeholder? (Note: A direct stakeholder directly interacts with a technology whereas an indirect stakeholder is impacted by a technology but does not directly interact with it.) Give your value scenario a short and compelling title. With a set of 3-5 bullet points, note the key features of your value scenario.
- Explore remedies, technical requirements, and regulations. Given the value scenario, step back and consider what technical features and regulations might be developed so Internet-connected devices in the smart home are less likely to be used in gaslighting attacks. Outline 2-3 technical requirements and 2-3 policy guidelines that might enable.
Document the results of your process on a single sheet of poster paper. Cover the following topics:
- Technical features and their connections
- Key direct and indirect stakeholders
- 2-3 technical requirements and 2-3 policy guidelines
Introduce your poster and your value scenario in a 5-minute presentation. After your presentation allow for 5-10 minutes for discussing your design solution.
Consider the following discussion questions:
- How, if at all, does your value scenario show that regulations of smart home technologies are necessary?
- How do your proposed technical requirements for a smart home relate to your proposed regulations? Are they each in their own separate spheres or do they intersect?
- What responsibilities do software and hardware engineers have for ensuring that smart home technology is not used for harm? What possible actions might an engineer take if she identifies a feature in a device that might be exploited by an attacker? See Tarnoff (2018) for some noteworthy examples where employees have resisted management.
Reflective writing prompts and exercises
- Do you agree with the claim that: “The difference between an IoT [Internet of Things] that enhances society and one that diminishes it will be determined by our ability to create an effective model for IoT governance” (Berman & Cerf, 2017)? Please discuss.
- Suppose the parents of an adolescent suspect that she is experimenting with drugs. How might the Internet of Things be used as a tool for investigating this possibility and for controlling the behavior of the adolescent? Would this use of smart technology be appropriate? What might be gained? What might be lost?
- Discuss how this applies to the Internet of Things: “technology is neither good nor bad; nor is it neutral.”
Notes and further reading
- The New York Times quotation comes from Manjoo (2018).
- For an introduction to the Internet of Things see FTC Staff Report (2015).
- For a short discussion of the possible benefits of IT Governance, see Berman & Cerf (2017).
- The number of expected objects in the Internet of Things comes from Statista (n.d.).
- Stenquist (2018) describes cars with communication functions that simplify purchasing things and services, saving people time.
- Data collected from automatic license plate readers have been used to identify welfare fraud and for other such purposes but at the cost of individual privacy and perhaps in ways that violate law (Maass, 2018; Fussel, 2018).
- Soper (2018) provides a brief introduction to Amazon Go. See also González (2016).
- The reported number of new Amazon Go stores comes from Super (2018).
- On the use of facial recognition technology to improve efficiency in lines, see Alan (2018).
- Cook (2018) reports on a patent awarded to Amazon that identifies illness based on the qualities and affect of a speaker’s voice.
- Hauser, C. (2018) reports on the police using Fitbit data as evidence for identifying and charging a murderer.
- The questions that might be answered at a “Smart Farm” comes from Sigfox. (n.d.).
- For IBM’s public service announcement related to home routers, see FBI (2018).
- For more on the 2016 Dyn Cyberattack, see 2016 Dyn Cyberattack – Wikipedia (n.d.).
- For more on Internet of Things botnet threats, see Weagle (2018).
- The New York Times reports that smart homes are being used in domestic abuse cases (Bowles, 2018).
- Gaslighting was first described by Barton & Whitehead (1969). See also Cawthra, O’Brien, & Hassanyeh (1987).
2016 Dyn cyberattack – Wikipedia. (n.d.). Retrieved October 7, 2018, from https://en.wikipedia.org/wiki/2016_Dyn_cyberattack
FTC Staff Report (2015). Internet of Things: Privacy & Security in a Connected World. Retrieved October 16, 2018, from https://www.ftc.gov/system/files/documents/reports/federal-trade-commission-staff-report-november-2013-workshop-entitled-internet-things-privacy/150127iotrpt.pdf
Alan, L. (2018, October 15). TSA bringing facial recognition to airport security lanes | The Seattle Times. Retrieved October 16, 2018, from https://www.seattletimes.com/business/tsa-bringing-facial-recognition-to-airport-security-lanes/
Barton, R., & Whitehead, J. A. (1969). The Gas-Light Phenomenon. The Lancet, 1, 1258–1266.
Berman, F. And Cerf, V. G. (2017). Social and ethical behavior in the Internet of Things. Communications of the ACM, 60(2), 6-7.
Bowles, N. (2018, June 23). Thermostats, Locks and Lights: Digital Tools of Domestic Abuse – The New York Times. Retrieved October 17, 2018, from https://www.nytimes.com/2018/06/23/technology/smart-home-devices-domestic-abuse.html
Cawthra, R., O’Brien, G., & Hassanyeh, F. (1987). ‘Imposed Psychosis’: A Case Variant of the Gaslight Phenomenon. British Journal of Psychiatry, 150(4), 553-556. http://doi.org/10.1192/bjp.150.4.553
Cook, J. (2018, October 9). Amazon patents new Alexa feature that knows when you’re ill and offers you medicine. Retrieved October 12, 2018, from https://www.telegraph.co.uk/technology/2018/10/09/amazon-patents-new-alexa-feature-knows-offers-medicine/
FBI. (2018, May 25). Internet Crime Complaint Center (IC3) | Foreign Cyber Actors Target Home and Office Routers and Networked Devices Worldwide [Public Service Announcement]. Retrieved October 11, 2018, from https://www.ic3.gov/media/2018/180525.aspx
Fussel, S. (2018, October 16). In Fraud Detection, Everything You Do Online and Off Is a Clue. The Atlantic. Retrieved from https://www.theatlantic.com/technology/archive/2018/10/online-fraud-detection-surveillance/573175/
González, Á. (2016, December 5). Amazon unveils smart convenience store sans checkouts, cashiers | The Seattle Times. Retrieved from https://www.seattletimes.com/business/amazon/amazoncom-unveils-self-driving-brick-and-mortar-convenience-store/
Hauser, C. (2018, October 3). Police Use Fitbit Data to Charge 90-Year-Old Man in Stepdaughter’s Killing – The New York Times. Retrieved October 7, 2018, from https://www.nytimes.com/2018/10/03/us/fitbit-murder-arrest.html
Kranzberg, M. (1986). Kranzberg’s laws. Technology and Culture, 27, 544-560.
Maass, D. (2018, July 31). County Welfare Office Violated Accountability Rules While Surveilling Benefits Recipients | Electronic Frontier Foundation. Retrieved October 17, 2018, from https://www.eff.org/deeplinks/2018/07/county-welfare-office-violated-accountability-rules-while-surveilling-benefits
Manjoo, F. (2018, October 10). A Future Where Everything Becomes a Computer Is as Creepy as You Feared – The New York Times. Retrieved October 11, 2018, from https://www.nytimes.com/2018/10/10/technology/future-internet-of-things.html
Sigfox. (n.d.). Retrieved October 17, 2018, from https://www.sigfox.com/en/agriculture
Soper, S. (2018, September 19). Amazon Said to Plan Up to 3,000 Cashierless Stores by 2021 – Bloomberg. Retrieved October 7, 2018, from https://www.bloomberg.com/news/articles/2018-09-19/amazon-is-said-to-plan-up-to-3-000-cashierless-stores-by-2021
Statista. (n.d.). IoT: number of connected devices worldwide 2012-2025. Retrieved October 4, 2018, from https://www.statista.com/statistics/471264/iot-number-of-connected-devices-worldwide/
Stenquist, P. (2018, October 14). Order a coffee and pay, with a tap on your car’s dash | The Seattle Times. Retrieved October 16, 2018, from https://www.seattletimes.com/business/order-a-coffee-and-pay-with-a-tap-on-your-cars-dash/
Tarnoff, B. (2018, August 9). Can Silicon Valley workers rein in Big Tech from within? | Ben Tarnoff | Opinion | The Guardian. Retrieved October 15, 2018, from https://www.theguardian.com/commentisfree/2018/aug/09/silicon-valley-tech-workers-labor-activism
Weagle, S. (2018, January 30). The Rise of IoT Botnet Threat and DDoS attacks | Corero. Retrieved October 17, 2018, from https://www.corero.com/blog/870-the-rise-of-iot-botnet-threats-and-ddos-attacks.html