The fiercest public health crisis in a century has elicited cooperative courage and sacrifice across the globe. At the same time, the COVID-19 pandemic is producing severe social, economic, political, and ethical divides, within and between nations. It is reshaping how we engage with each other and how we see the world around us. It urges us to think more deeply on many challenging issues—some of which can perhaps offer opportunities if we handle them well. The transcripts that follow speak to the potency and promise of dialogue. They record two in a continuing series of “COVID-19 In Conversations” hosted by Oxford Prospects and Global Development Institute.
Digital discrimination is becoming a serious problem, as more and more decisions are delegated to systems increasingly based on artificial intelligence techniques such as machine learning. Although a significant amount of research has been undertaken from different disciplinary angles to understand this challenge—from computer science to law to sociology— none of these fields have been able to resolve the problem on their own terms. We propose a synergistic approach that allows us to explore bias and discrimination in AI by supplementing technical literature with social, legal, and ethical perspectives.
When we see a built world, we tend to take its permanence and stability for granted. For those who have chosen coastal homes, that built world goes back at least 50 years, with few residents ever realizing that oceans, lakes, and rivers are living entities constantly in motion. The average person relies upon experts such as architects and civil engineers, and supposed guardrails such as state building codes and homeowner associations, to assess safety when purchasing property. But the 21st-century assumption that the built world is stable is a risky bet. Especially in “business-friendly” states.
Just as the “autonomous” in lethal autonomous weapons allows the military to dissemble over responsibility for their effects, there are civilian companies leveraging “AI” to exert control without responsibility.
And so we arrive at “trustworthy AI” because, of course, we are building systems that people should trust and if they don’t it’s their fault, so how can we make them do that, right? Or, we’ve built this amazing “AI” system that can drive your car for you but don’t blame us when it crashes because you should have been paying attention. Or, we built it, sure, but then it learned stuff and it’s not under our control anymore—the world is a complex place.
https://21stcenturywiener.org/ 22-25 July 2021, Chennai, INDIA N R Narayana Murthy to present Opening Speech on 22 July 2021. Infosys co-founder… Read More
Open technology communities are loosely organized, volunteer, online groups, focused on development and distribution of open or free software and hardware. “Hacking Diversity:The Politics of Inclusion in Open Technology Cultures” is a study of the efforts of open technology communities to “hack” the issues around the lack of diversity that pervades not only their volunteer communities, but also their related disciplines at large.
There is huge potential for artificial intelligence (AI) to bring massive benefits to under-served populations, advancing equal access to public services such as health, education, social assistance, or public transportation, AI can also drive inequality, concentrating wealth, resources, and decision-making power in the hands of a few countries, companies, or citizens. Artificial intelligence for equity (AI4Eq) calls upon academics, AI developers, civil society, and government policy-makers to work collaboratively toward a technological transformation that increases the benefits to society, reduces inequality, and aims to leave no one behind.
From the 1970s onward, we started to dream of the leisure society in which, thanks to technological progress and consequent increase in productivity, working hours would be minimized and we would all live in abundance. We all could devote our time almost exclusively to personal relationships, contact with nature, sciences, the arts, playful activities, and so on. Today, this utopia seems more unattainable than it did then. Since the 21st century, we have seen inequalities increasingly accentuated: of the increase in wealth in the United States between 2006 and 2018, adjusted for inflation and population growth, more than 87% went to the richest 10% of the population, and the poorest 50% lost wealth .
Unless we create real boundaries, enforced by legislation, the social media giants will also walk away from the chaos they have enabled.
Understanding the societal trajectory induced by AI, and anticipating its directions so that we might apply it for achieving equity, is a sociological, ethical, legal, cultural, generational, educational, and political problem.
Abstract Since 2016, drones have been deployed in various development projects in sub-Saharan Africa, where trials, tests, and studies have… Read More
Video doorbells and related technologies, along with the data they generate, will continue to be abused, undermining the security of what is being pitched as a security technology.
For better or worse, we have become familiar with the idea that technologies profile people to deliver a service of… Read More
We can perhaps accept Weil’s starting premise of obligations as fundamental concepts, based on which we can also reasonably accept her assertion that “obligations … all stem, without exception, from the vital needs of the human being.”
Examining how face recognition software is used to identify and sort citizenship within mechanisms like the Biometric Air Exit (BAE) is immensely important; alongside this, the process of how “citizen” and “noncitizen” is defined, as data points within larger mechanisms like the BAE, need to be made transparent.
Public Interest Technology (PIT) is defined as “technology practitioners who focus on social justice, the common good, and/or the public… Read More
Albright’s book focuses on a group of Americans who live a life of digital hyper-connectivity. Mostly under age 50, this would include what are called Generation X (born between 1965 and 1979), Millennials (born between 1980 and 1999), and their offspring — some, as we have seen, still infants.
Contemporary circumstances in the United States, both in broader politics, recent protest movements around police brutality, and in the demographics of engineering education, have prompted us to look for new ways to bring theory on gender, race, and class to audiences who would not normally consider it their usual reading.
Technological determinism is a myth; there are always underlying economic motivations for emergence of new technologies. The idea that technology leads development is not necessarily true, for example, con-sider AI. It has been a topic of inter-est to researchers for decades, but only recently has the funding caught up, matching the motivation and enabling the development of AI-ori-ented technologies to really take off.
Why are all of these nations and their assorted consortia heading to Mars? Are they truly exploring to improve the human condition, to expand and share scientific knowledge?