Ethical Tech Startup Guide, published by Springer Nature, draws on almost five decades of entrepreneurial experience and innovation and offers a broad perspective on ethical tech startups. It approaches the subject on two fronts by considering both the business of ethical technology as well as the challenges of tech startups with an imperative to behave ethically.
The book is a clear and concise presentation of principles for ethical tech startup success, with recommendations are grounded in the experiences of 26 example firms and the entrepreneurs whose leadership and skill animated them.
Ben Shneiderman is an Emeritus Distinguished University Professor in the Department of Computer Science at the University of Maryland, and a much-honoured pioneer in the field of Human-Computer Interaction. His recent book, Human-Centered AI, is a valuable contribution to the literature discussing challenges for the appropriate use of artificial intelligence and proposing approaches and steps to achieve a safer and more humane future incorporating the likely increased use of AI.
Although there is much that I could discuss, I shall focus primarily on Part 3, Design Metaphors, and Part 4, Governance Structures.
C. Dianne Martin is Emeritus Professor of Computer Science at George Washington University, and Adjunct Professor in the School of Information, University of North Carolina at Chapel Hill. She has been teaching Computers and Society since 1983.
In 1787 Jeremy Bentham, the British Utilitarian philosopher and penal reform theorist, wrote a series of letters in which he proposed a Panopticon (all-seeing), also called The Inspection-House. His letters put forward “the idea of a new principle of construction applicable to any sort of establishment, in which persons of any description are to be kept under inspection”. For the next 16 years he was obsessed with the desire to implement his model prison design, which he believed would transform penal methods by drastically cutting cost through significant downsizing of the workforce needed to oversee prison populations. He also felt such prisons would have positive moral value to the prisoners.
Emerging—and existing—technologies are bringing us closer to the brink. And even if they turn out to be more benign, envisioning some technological advance as our salvation will waste precious time as the ecosystems upon which we rely move closer to collapse and the violent forces of authoritarianism gain power.
All technology, from hammers and hummers to routers and killer robots, is intended to increase power: to do something cheaper, easier, faster, with more entertainment value, with stronger impact, at greater distances, in more places, or with greater stealth. Technological power, like economic, political, cultural, institutional, or physical power, is distributed unevenly. It tends to be accumulated by people and organizations who already have too much. Algorithmic power has accelerated those differences; the computer has helped create today’s staggering economic divide. Many of the world’s richest people gained their fortunes through such algorithms, and it is their ideologies as well as the computer systems themselves that are taking us in dangerous directions.
Digital technologies for learning, health, politics, and commerce have enriched the world. Digital heroes like Sir Tim Berners-Lee, Batya Friedman, Alan Kay, JCR Licklider, and Joe Weizenbaum have blazed trails. Yet there is trouble. We depend upon software that nobody totally understands. We are vulnerable to cyberterrorism. Privacy is overrun by surveillance capitalism.Totalitarian control advances. Daily internet news matching our beliefs makes it hard to tell true from false. People are addicted to devices. Jobs disappear without social safety nets. Digital leviathans threaten to control all commerce. Our values are threatened.
There are risks of premature use of AI in domains such as health, criminal justice, senior care, and warfare. Much current AI is unreliable, without common sense, deceptive in hiding that it’s an algorithm, unable to explain decisions, unjust, neither accountable nor responsible, and untrustworthy.
The number of seniors is growing rapidly worldwide. The population of adults aged 60 years and over will grow from 901 million in 2015 to 1.4 billion in 2030 and 2.1 billion in 2050. The number of ‘oldest old’ — those aged 80 years and older — will grow from 125 million in 2015 to 434 million in 2050. Declining birth rates reduce the Caregiver Support Ratio, the ratio of available caregivers to those who need care, hence adequate care for older adults is often lacking.
In the USA, the number of potential family caregivers aged 45 to 64 divided by the number of oldest old is projected to decline from more than seven in 2010 to less than three by 2050. It is hard to find and train good paid caregivers — many are ‘imported’ from other countries such as the Philippines. Hence there are too few people to care for growing numbers of seniors. Many caregivers are also illegal immigrants; U.S. policies made the situation there worse. The problem is more dire in some other countries. Japan’s population aged 65 and over is projected to grow from a current level of 25% to 40% by 2055. The country will need to add one million senior care workers and nurses by then.
Brett Frischmann is the Charles Widger Endowed University Professor in Law, Business and Economics, Villanova University. His most relevant book to his thoughts below is Re-Engineering Humanity (Cambridge University Press 2018).
Q: What do you do when you see a little button on a webpage or app screen that says I agree? A: Click the button.
The familiar and incredibly simple click-to-agree mechanism is ubiquitous. We encounter it throughout our digital lives. It is nothing less than the “legal backbone” of the Internet, app stores, e-commerce, and so much more. Yet electronic contracting and the illusion of consent-by-clicking are a sham!
In a recent blog, I discussed digital technology’s contribution to the environmental apocalypse, with massive amounts of energy being used in three ways: (1) to manufacture digital technologies; (2) to operate them; and (3) to dispose of and replace them with newer versions.
Electronic waste (e-waste) occurs when repair of electrical and electronic equipment (EEE) is impossible or undesirable and where devices are discarded thoughtlessly. A 2020 estimate of the amount of e-waste produced in the world was 54 million metric tons, which amounts to 7.3 kg fo every person in the world. Who would have predicted that the figure would be so high? The amount is doubling every 16 years. Asia generates the greatest quantity, followed by the Americas and Europe, which also produces the most per person.
AI and in particular machine learning has made great progress in the last decade. Yet I am deeply concerned about the hype associated with AI, and the risks to society stemming from premature use of the software. We are particularly vulnerable in domains such as medical diagnosis, criminal justice, seniors care, driving, and warfare. Here AI applications have begun or are imminent. Yet much current AIs are unreliable and inconsistent, without common sense; deceptive in hiding that they are algorithms and not people; mute and unable to explain decisions and actions; unfair and unjust; free from accountability and responsibility; and used but not trusted.
Imagine a world governed by smart technologies engineered to achieve three distinct yet interrelated normative ends: optimized transactional efficiency, resource productivity and human happiness. We could have congestion-free roads—no stop and go, no road rage! Instantaneous, personalized entertainment—no need to search or browse! Successful social interactions—no misunderstanding or missed cues! No surprise ailments, no failures, no missed opportunities! Heck, no surprises of any kind! There are so many imperfections in our world that smart technology could fix.
We do not live in such a world, but the technologies required for it to exist are already being rapidly developed and deployed. Take, for example, the Internet of Things (IoT)—big data, sensors, algorithms, artificial intelligence and various other related technologies. Their promoters make seductive promises. Supposedly, smart phones, grids, cars, homes, clothing and so on will make our lives easier, better, happier.