IoT and AI push tech ethics to the forefront of development

AI and IoT sensors have tied humans and machines closer than ever without much hesitation, but organizations must learn to apply ethics in technology development.

Data breaches and privacy scandals have made it vital for organizations to prioritize tech ethics and consider the effects IoT devices and AI will have on individuals and society.

The biggest challenges facing today's technologies aren't technological -- they are human. Humans dictate adoption and abuse, determine the calculus of value and define governance.

The previous article of this series analyzed three human issues: privacy, biometric authentication and the notion of ownership. IT pros can expand their assessment of technology's effect on society with three additional topics: tech ethics, new interfaces and the rise of anthropomorphic machines.

'Tech ethics' is today's buzzword and business imperative

With revelations of fake news and mass manipulation, ever more pernicious cyberthreats and privacy breaches as well as calls for regulation, 2018 marked a new chapter. Now more than ever, the mass automation of big data, ubiquitous sensing and machines' ability to learn call for a new business competency: a formalized and grounded approach to tech ethics.

Components of digital ethics

Tech ethics has entered mainstream societal discourse, and most companies are scrambling to organize -- never mind reconcile risks with revenue implications. Kaleido Insights researchers found more and more companies hire C-suite ethics officers, appoint internal and external ethics advisory boards, join industry coalitions -- such as Partnership on AI -- or develop interdepartmental working groups. Regardless of the structure, the objective is to shift from mere risk avoidance to forward-thinking planning and counter-efforts across key areas, including design, data protection, content moderation, guidelines and processes, and training.

Emerging interfaces build tomorrow's internet interactions

The most profound advancements in technology are often less about technology and more about new interfaces replacing old ones. The car offered an entirely new interface to mobility than a horse; the telephone did the same for communications; databases replaced filing cabinets. Consider how mobile has already transformed media and commerce.

Businesses' ethical preparedness around AI and other emerging tech starts upstream by cultivating ethics in the culture of the organization.

IoT sensors and networking technology expand the definition of digital from just personal computers and mobile, to include objects, machines and infrastructure, and AI is digitizing the ways people interact. IT pros do not just impose data streams to objects; they transform the very interface of data collection.

IT pros are just awakening to the implications of this shift. Talking to machines may well be more convenient than typing and tapping, but digitizing voice opens new considerations. A person's voice is uniquely identifiable. Even voice data samples offer intimate health information such as fatigue, arousal, intoxication, PTSD or depression, not to mention breath data, whose chemical exhalation contains unique biomarker signatures, which can indicate specific diseases.

Beyond voice, emerging interaction modalities are integrating our bodies into digital interface, analyzing our faces, our emotions, our eyes, our skin, our fingerprints, our pulses. Retailers' cameras, kiosks and robotics are detecting faces for in-store customer analysis and crime prevention. Auto manufacturers are developing emotion recognition to detect fatigue and stress. Tech and fashion giants partner on glasses, earphones, garments and shoes that bring augmented reality to customers, such as the partnership of Facebook and Luxottica eyewear company to create augmented reality Ray-Bans.

Anthropomorphic machines shape empathic computing and future decision-making

The shift in interface brought about by sensing and AI also signals a renaissance in human-machine interactions. Humanoid robotics have long been sci-fi darlings and designer aspirations, but thanks to big data plus emotion and speech recognition, they are becoming the norm. In robotics, and increasingly in formless AI applications like chatbots or virtual agents, developers train software to analyze our every cue -- behavioral and biometric -- to recognize and engage us based on our particular feelings.

According to Global Market Insights, the global intelligent virtual assistant market is poised for a 30% compound annual growth rate in the next five years. Conversational, always-personalizing and always-available bots are jumping from smartphones and speakers to toys, headphones, cars, workplaces and beyond. People clutch their smartphones today, but imagine if software agents were children's earliest playmates, forgiving tutors, witty advocates in the search for a job or a date or the go-to for council. A digital companion would have years of individualized data, including every search, step, share, location, handshake, level of stimulation, breath, transaction and thousands of other data points.

What happens when humans become so empowered by virtual agents and robotics that they become emotionally, socially or occupationally reliant? People's relationships with machines will shift as AI infuses both consumer products and enterprise decision-making, and as AI itself learns how humans respond, emote and work.

Implement best practices for tech ethics

Across these areas, Kaleido Insights' research surfaces best practices applicable to every business:

Develop core roles and infrastructure for responsible use. Businesses' ethical preparedness around AI and other emerging tech starts upstream by cultivating ethics in the culture of the organization, identifying risks and legal issues, empowering people to do the right thing and addressing issues with transparency, even if other corporate pressures may run counter.

Evaluate and articulate the trade-offs of new interfaces. Organizations must consider the effects of using our bodies to interface with devices -- not only effects in data collection or monetization, but in security, privacy, compliance and society. Informed consent is underscored in the context of our biometric and health data.

Prioritize more diverse metrics, especially around user health. Profits are critical, but not the only metric of success in digital ecosystems. Organizations must define and align against holistic metrics around user goals, user and community health, security, safety and related efficiencies, advancements and fiduciary responsibilities.

Now more than ever, providers of IoT-based devices and experiences play an integral role, not only in addressing these issues, but helping influence outcomes, market forces and societal health.

Next Steps

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