Abstract
Abstract
Our social relations are changing, we are now not just talking to each other, but we are now also talking to artificial intelligence (AI) assistants. We claim AI assistants present a new form of digital connectivity risk and a key aspect of this risk phenomenon is related to user risk awareness (or lack of) regarding AI assistant functionality. AI assistants present a significant societal risk phenomenon amplified by the global scale of the products and the increasing use in healthcare, education, business, and service industry. However, there appears to be little research concerning the need to not only understand the changing risks of AI assistant technologies but also how to frame and communicate the risks to users. How can users assess the risks without fully understanding the complexity of the technology? This is a challenging and unwelcome scenario. AI assistant technologies consist of a complex ecosystem and demand explicit and precise communication in terms of communicating and contextualising the new digital risk phenomenon. The paper then argues for the need to examine how to best to explain and support both domestic and commercial user risk awareness regarding AI assistants. To this end, we propose the method of creating a risk narrative which is focused on temporal points of changing societal connectivity and contextualised in terms of risk. We claim the connectivity risk narrative provides an effective medium in capturing, communicating, and contextualising the risks of AI assistants in a medium that can support explainability as a risk mitigation mechanism.
- How the GDPR will change the worldEur Data Prot L Rev20162287Google Scholar
Cross Ref
- Alzahrani H (2016) Artificial intelligence: uses and misuses. Glob J Comput Sci Technol 16(1)Google Scholar
- Amazon Press Release (2017) http://phx.corporate-ir.net/phoenix.zhtml?c=176060&p=irol-newsArticle&ID=2324045. Accessed June 2018Google Scholar
- Amazon.com Help: Alexa Terms of Use (2019) https://www.amazon.com/gp/help/customer/display.html?nodeId=201809740. Accessed July 2019Google Scholar
- Big data surveillance: introductionSurveill Soc2014122185196Google Scholar
- The personalization privacy paradox: an empirical evaluation of information transparency and the willingness to be profiled online for personalizationMIS Q2006301132810.2307/25148715Google Scholar
Cross Ref
- From semi to fully autonomous vehicles: new emerging risks and ethico-legal challenges for human-machine interactionsTransp Res Part F Traffic Psychol Behav201963153164Google Scholar
Cross Ref
- The privacy paradox–investigating discrepancies between expressed privacy concerns and actual online behavior—a systematic literature reviewTelemat Inform201734710381058Google Scholar
Digital Library
- Barth A, Datta A, Mitchell JC, Nissenbaum H (2006) Privacy and contextual integrity: framework and applications. In: 2006 IEEE symposium on security and privacy (S&P'06). IEEE, p 15Google Scholar
- Big data in health care: using analytics to identify and manage high-risk and high-cost patientsHealth Aff201433711231131Google Scholar
Cross Ref
- Emerging risks of violence in the digital ageJ Sch Violence2002125171Google Scholar
Cross Ref
- Big data and specific analysis methods for insurance fraud detectionDatabase Syst J2013443039Google Scholar
- Personal data v. Big data: challenges of commodification of personal dataOpen J Philos201883206215Google Scholar
- On the track of artificial intelligence: learning with intelligent personal assistantsJ New Results Sci2016131592601Google Scholar
- The big data debateScience20143466211818Google Scholar
- Chung H, Park J, Lee S (2017) Digital forensic approaches for Amazon Alexa ecosystem. Digital investigation, vol 22. https://sciencedirect.com/science/article/pii/s1742287617301974. Retrieved 22 Aug 2019Google Scholar
- Crandall J, Song P (2013) A pointillism approach for natural language processing of social media. arXiv (Information Retrieval)Google Scholar
- Cunneen M, Mullins M, Murphy F, Shannon D, Furxhi I, Ryan C (2019) Autonomous vehicles and avoiding the trolley (dilemma): vehicle perception, classification, and the challenges of framing decision ethics. Cybern Syst 1–22Google Scholar
- The limits of intelligent personal assistantsNat Lang Eng2015212325329Google Scholar
- The pros and cons of listening devicesNat Lang Eng2017236969973Google Scholar
- What works best: objective statistics or a personal testimonial? An assessment of the persuasive effects of different types of message evidence on risk perceptionHealth Psychol2008271110115Google Scholar
- Equity, safety, and privacy in the autonomous vehicle eraIEEE Comput201649118083Google Scholar
Digital Library
- Prescriptive scientific narratives for communicating usable scienceProc Natl Acad Sci USA20141111362713633Google Scholar
- Helen Nissenbaum, privacy in context: technology, policy, and the integrity of social lifeJ Value Inqui2011451971021112650Google Scholar
- Floridi L (2019) Translating principles into practices of digital ethics: five risks of being unethical. Philos Technol 1–9Google Scholar
- Personal and social factors involved in internet addiction among adolescents: a meta-analysisComput Human Behav201886387400Google Scholar
- Evaluating risk communication: narrative vs. Technical presentations of information about radonRisk Anal19921212735Google Scholar
- Gray S (2016) Always on: privacy implications of microphone-enabled devices. In: Future of privacy forumGoogle Scholar
- Social contract 2.0: terms of service agreements and political theoryJ Media Crit20141145168Google Scholar
- Making AI safe for humans: a conversation with Siri2017LondonRoutledge6985Google Scholar
- Hasebrink U, Goerzig A, Haddon L, Kalmus V, Livingstone S (2011) Patterns of risk and safety online: in-depth analyses from the EU Kids Online survey. https://core.ac.uk/download/pdf/221597.pdf. Accessed Apr 2019Google Scholar
- Will democracy survive big data and artificial intelligence? Towards digital enlightenment2019ChamSpringer7398Google Scholar
- Henwood K, Pidgeon N, Parkhill K, Simmons P (2011) Researching risk: Narrative, biography, subjectivity. Hist Soc Res/Historische Sozialforschung 36(4):251–272Google Scholar
- Mixed methods research synthesis: definition, framework, and potentialQual Quant2013472659676Google Scholar
- Slaves to big data. Or are we?Rev Internet Derecho Política201317744Google Scholar
- Smart technologies and the end (s) of law: novel entanglements of law and technology2015LondonEdward Elgar PublishingGoogle Scholar
Cross Ref
- The value of personal data. Digital enlightenment yearbook 20132013AmsterdamIOS PressGoogle Scholar
Digital Library
- Janeček V (2018) Ownership of personal data in the internet of things (December 1, 2017). Comput Law Secur Rev 34(5):1039–1052. 10.2139/ssrn.3111047Google Scholar
- Cyberthreats under the BedComputer20185159295Google Scholar
- Lopatovska I, Rink K, Knight I, Raines K, Cosenza K, Williams H, Sorsche P, Hirsch D, Li Q, Martinez A (2018) Talk to me: exploring user interactions with the Amazon Alexa. J Librariansh Inf Sci 96100061875941Google Scholar
- Digital risk societyThe Routledge hand-book of risk studies2016LondonRoutledge301309Google Scholar
- Narratives of riskJ Risk Res200811141542439792Google Scholar
- Marchant GE, Allenby BR, Herkert JR (2011) The growing gap between emerging technologies and legal-ethical oversight: the pacing problem. In: The international library of ethics, law and technologyGoogle Scholar
- Digital literacy and the digital societyDigit Literacies Concepts Policies Pract200830151176Google Scholar
- Why privacy is not enough privacy in the context of “ubiquitous computing” and “big data”J Inf Commun Ethics Soc201412293106Google Scholar
Cross Ref
- Hey Alexa… examine the variables influencing the use of artificial intelligent in-home voice assistantsComput Hum Behav2019992837Google Scholar
Digital Library
- Illusions of balance and control in an always-on environment: a case study of BlackBerry usersContinuum2007212165178Google Scholar
Cross Ref
- Mitchell MC, Egudo M (2003) A review of narrative methodology (no. DSTO-GD-0385). Def Sci Technol Organ Edinb (Australia) Land Oper DivGoogle Scholar
- Mote K (2012) Natural language processing - a survey. Computation and language. arXiv:1209.6238Google Scholar
- Natural language processing: an introductionJ Am Med Inform Assoc2011185544551Google Scholar
Cross Ref
- Privacy as contextual integrityWash Law Rev2004791119157Google Scholar
- Nissenbaum H (2017) Deregulating collection: must privacy give way to use regulation? Soc Sci Res NetwGoogle Scholar
- Reflections on risk perception and policy 1,2Risk Anal1982226982Google Scholar
- Evaluation and aggregation of pay-as-you-drive insurance rate factorsDecis Support Syst201356192201Google Scholar
Digital Library
- Privacy as a luxury commodityFirst Monday20101582Google Scholar
- Regulating risk: defining genetic privacy in the United States and BritainSci Technol Hum Values2004293332352Google Scholar
- Social media and cookies: challenges for online privacyInfo20111363042Google Scholar
Cross Ref
- Asking ‘Why’ in AI: explainability of intelligent systems—perspectives and challengesIntell Syst Account Financ Manag201825637210.1002/isaf.1422Google Scholar
Digital Library
- Rosen J (2012) The right to be forgotten. Stanford Law Review. Available from http://www.stanfordlawreview.org/online/privacy-paradox/right-to-be-forgotten. Accessed 14 Nov 2018Google Scholar
- Humanizing human–robot interaction: on the importance of mutual understandingIEEE Technol Soc Mag20183712229Google Scholar
Cross Ref
- Turkle S (2006) Always-on/Always-on-you: the tethered self. Handbook of mobile communication studies, 121Google Scholar
- In good company? On the threshold of robotic companions. Close engagements with artificial companions: key2010AmsterdamJohn BenjaminsGoogle Scholar
- The tethered self: technology reinvents intimacy and solitudeContin High Educ Rev20117529Google Scholar
- Van Loon J (2003) Risk and technological culture: towards a sociology of virulenceGoogle Scholar
- Venkatadri G, Andreou A, Liu Y, Mislove A, Gummadi KP, Loiseau P, Goga O (2018) Privacy risks with facebook’s PII-based targeting: auditing a data broker’s advertising interface. In: 2018 IEEE symposium on security and privacy (SP). IEEE, pp 89–107Google Scholar
- ELIZA—a computer program for the study of natural language communication between man and machineCommun ACM1966913645Google Scholar
Digital Library
- Zuboff S (1988) Dilemmas of transformation in the age of the smart machine. PUB TYPE 81Google Scholar
- The emperor’s new information economyInformation technology and changes in organizational work1996Boston, MASpringer1317Google Scholar
- Zuboff S (2019) Surveillance capitalism and the challenge of collective action. In: New labor forum, vol 28, No. 1. SAGE Publications, Sage, Los Angeles, CA, pp 10–29Google Scholar
Recommendations
Artificial Intelligence and Risk in Design
DIS '20: Proceedings of the 2020 ACM Designing Interactive Systems ConferenceAs artificial intelligence (AI) technologies are more and more integrated into everyday lives, both scholarly and popular discourses on AI's often revolve around charting the various risks that may be associated with them. The manner and magnitude of ...
The role of experts in the public perception of risk of artificial intelligence
AbstractThe goal of this paper is to describe the mechanism of the public perception of risk of artificial intelligence. For that we apply the social amplification of risk framework to the public perception of artificial intelligence using data collected ...
Perceived Risk Attitudes: Relating Risk Perception to Risky Choice
This paper provides empirical evidence that distinguishes between alternative conceptualizations of the risky decision making process. Two studies investigate whether cross-situational differences in choice behavior should be interpreted in the expected ...
Comments