The first Artificial Intelligence ever created was Pandora, a creation of the Greek gods Hephaestus and Athena. Pandora means both "all-gifted" and "all-giving" and was constructed with attributes from every other Olympian god. Pandora was created at the request of Zeus, the king of the gods, as a punishment for Prometheus stealing fire, the first disruptive technology, and handing it over to mankind. Zeus punishes Prometheus, the proto-god of technology and intelligence, for giving fire to mankind by chaining him to a rock, and he punishes mankind by giving them Pandora, the first A.I., who has been endowed with attributes from all of the gods. But how is this gift a punishment?

Lets imagine for a moment that the horse you see in the image below is sick and dying.

For those engaged in advocacy around the social harms of AI systems, a definitional exercise could, however, be a key way to rescue AI from the abstract, and foreground social and material concerns around these systems. Just as glossy data visualizations can obscure the unequal impacts and governance failures of the pandemic, AI as an abstract buzzword can be brandished against complex social problems as if it were a neutral and external'solution' rather than a sociotechnical system 14 designed and developed to make value-laden choices and trade-offs.

This paper explores the hypothesis that the diversity of human languages, right now a barrier to interoperability in communication and trade, will become significantly less of a barrier as machine translation technologies are deployed over the next several years.But this new boundary-breaking technology does not reduce all boundaries equally, and it creates new challenges for the distribution of ideas and thus for innovation and economic growth.

Artificial intelligence (AI) is set to greatly enhance the productivity and efficiency of global supply chains over the next decade. Transnational corporations are hailing these gains as a'game changer' for advancing environmental sustainability. Yet, looking through a political economy lens, it is clear that AI is not advancing sustainability nearly as much as industry leaders are claiming. As this article argues, the metrics and rhetoric of corporate social responsibility are exaggerating the benefits and obscuring the costs of AI. Productivity and efficiency gains in the middle sections of supply chains are rebounding into more production and consumption, doing far more to enhance the profitability of big business than the sustainability of the earth.

In their book The End of Capitalism (As We Knew It), J.K. Gibson-Graham, a two-person writing team, examine a conundrum: after innumerable examinations of capitalism's inherent contradictions, and despite decades of projects devoted specifically to accelerating its demise, capitalism seems as vibrant as ever. Gibson-Graham ask, "In the face of these efforts, how has capitalism maintained such a strong grip on political economy?" The answer they offer is oblique but striking: perhaps it hasn't. More precisely, they suggest that the conventional wisdom that economic life is dominated by capitalist relations is not, in fact, true. They point to the wide range of forms of economic engagement that fall outside the limits of traditional political economy -- domestic activity, relations of care, mutual support, self-sustenance, and more -- to argue that capitalism is only one amongst a range of concurrent forms of economic life -- and perhaps not even the most common.

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!

From driverless cars to online financial infrastructure payments, Artificial Intelligence obviously will be the heart of the next industrial revolution. The wave of globalisation and democracy cannot be overlooked regarding their contributions steering policy integration. Both concepts will play vital roles towards integrating the African continent under an umbrella perceived to end humanity (Artificial Intelligence). The rise of machines and robotics in high-income economies has been a contested discourse by philosophers, economists, tech geeks and policy makers. There is a rising belief it would steal jobs and render humanity useless and even economists seem not to be certain about the relevance of labour in this period. Immediately Japan was announced as the host of 2020 Olympics, what would strike one's mind is the presence of robotics during the famous sporting event.

'We can presume that the goal of the EAGIs is to emancipate themselves from human control while also participating in the world economy which would be the most efficient way to acquire necessary resources (using the economic means or political means or a mix of both?).' The last phrase refers to an observation made by Franz Oppenheimer in The State. Oppenheimer noted that there are only two means of acquiring the resources necessary for survival, the political means or the economic means. The political means involve the threat or use of violence and/or fraud. The economic means is peaceful, voluntary exchange.

Links between licit and illicit economies fuel conflict in countries mired in irregular warfare. We argue that in Afghanistan, cultivating poppy and trading drugs bring stability to farmers who face the unintended consequences of haphazard development efforts while lacking alternative livelihoods and security necessary to access markets. Drug trafficking funds the crime-insurgency nexus and government corruption, in turn foiling attempts to establish a unified governance body. We show how individual rationality, market forces, corruption and opium stocks accumulated at different stages in the supply chain counteract the effects of poppy eradication. To that end, we use initial results from a multiagent model of the Afghan drug industry. We define physical, administrative, social and infrastructural environments in the simulation, and outline objectives and inputs for decision making and the structure of actor interactions.