Category: Artificial Intelligence (AI)

Second International Workshop on Artificial Intelligence for Equity (AI4Eq) Against Modern Indentured Servitude

An element of the expansion of digital technologies is a shift in Artificial Intelligence (AI) technology from research laboratories into the hands of anyone with a smartphone. AI powered search, personalization and automation are being deployed across sectors, from education to healthcare, to policing, to finance. Wide AI diffusion is then reshaping the way organizations, communities and individuals’ function. The potentially radical consequences of AI have pushed nation states across the globe to publish strategies on how they seek to shape, drive and leverage the disruptive capabilities offered by AI technologies to bolster their prosperity and security.

Systems can be designed using methodologies like value-sensitive design, and operationalized, to produce socio-technical solutions to support or complement policies that address environmental sustainability, social justice, or public health. Such systems are then deployed in order to promote the public interest or enable users to act (individually and at scale) in a way that is in the public interest toward individual and communal empowerment.

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.

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.

The COVID-19 pandemic has exposed and exacerbated existing global inequalities. Whether at the local, national, or international scale, the gap between the privileged and the vulnerable is growing wider, resulting in a broad increase in inequality across all dimensions of society. The disease has strained health systems, social support programs, and the economy as a whole, drawing an ever-widening distinction between those with access to treatment, services, and job opportunities and those without.

We celebrated AI for mental health equity when access is augmented for marginalized populations. We applauded AI as a complement to current services; practitioners would be less overtaxed and more productive, thereby serving vulnerable populations better.

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

Introduction In 2019, IEEE Working Group P7014 began efforts to develop a ‘Standard for Ethical Considerations in Emulated Empathy in…  Read More

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 .

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.

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.

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.

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.

Ethical diversity refers to “diverse beliefs … as to what are the most ethically appropriate or inappropriate courses of actions,” and takes into account the different values and beliefs people hold [2]. This diversity is and has always been a source of confusion and conflict, from the personal to the international. The answer, however, is to have forums to debate and discuss the ethical choices embedded in everyday life, not algorithms that render the choice being made invisible.

Will We Make Our Numbers? The year 2020 has a majority of the planet asking the simple question: “How do we stay alive? Competition is not working for the long-term sustainability of human and environmental well-being.

As we work to decouple carbon emissions and economic growth on the path to net zero emissions — so-called “clean growth” — we must also meaningfully deliver sustainable, inclusive growth with emerging technologies.

While many of us hear about the latest and greatest breakthrough in AI technology, what we hear less about is its environmental impact. In fact, much of AI’s recent progress has required ever-increasing amounts of data and computing power. We believe that tracking and communicating the environmental impact of ML should be a key part of the research and development process.