In the last decades, there has been a deceleration in the rates of According to the World Bank [43], over six hundred and fifty million poverty reduction, suggesting that traditional redistributive approaches people (10% of the global population) still live in extreme poverty to poverty mitigation could be losing effectiveness, and and COVID-19 has particularly affected the poorest: the number alternative insights to advance the number one UN Sustainable of people living in extreme poverty rose by 11 % in 2020 [45]. In Development Goal are required. The criminalization of poor people this context, urgent and innovative measures are required to work has been denounced by several NGOs, and an increasing number towards poverty eradication, the number one UN Sustainable Development of voices suggest that discrimination against the poor (a phenomenon Goal. Traditional policies based on the redistribution of known as aporophobia) could be an impediment to mitigating wealth could be losing effectiveness, since there has been a deceleration poverty. In this paper, we present the novel Aporophobia in the poverty reduction rates throughout the last decades Agent-Based Model (AABM) to provide evidence of the correlation [12]. Artificial Intelligence tools can provide alternative insights to between aporophobia and poverty computationally. We present this global challenge.

Redistribution of resources within a group as a method to reduce wealth inequality is a current area of debate. The evolutionary path to or away from wealth sharing is also a subject of active research. In order to investigate effects and evolution of wealth sharing, societies are simulated using a minimal model of a complex adapting system. These simulations demonstrate, for this artificial foraging society, that local sharing of resources reduces the economy's total wealth and increases wealth inequality. Evolutionary pressures strongly select against local sharing, whether globally or within a individual's clan, and select for asocial behaviors. By holding constant the gene for sharing resources among neighbors, from rich to poor, either with everyone or only within members of the same clan, social behavior is selected but total wealth and mean age are substantially reduced relative to non-sharing societies. The Gini coefficient is shown to be ineffective in measuring these changes in total wealth and wealth distributions, and, therefore, individual well-being. Only with sociality do strategies emerge that allow sharing clans to exclude or coexist with non-sharing clans. These strategies are based on spatial effects, emphasizing the importance of modeling movement mediated community assembly and coexistence as well as sociality.

ChatGPT is just the latest technology to fuel worries that it will wipe out the jobs of millions of workers, whether advertising copywriters, Wall Street traders, salespeople, writers of basic computer code or journalists. But while many workforce experts say the fears that ChatGPT and other artificial intelligence (AI) technologies will cause unemployment to skyrocket are overblown, they point to another fear about AI: that it will widen the US's already huge income and wealth inequality by creating a new wave of billionaire tech barons at the same time that it pushes many workers out of better paid jobs. Like many revolutionary technologies before it, AI is likely to eliminate jobs. But, as has been the case in the past, experts argue, AI will likely offset much of that by spurring the creation of new jobs in addition to enhancing many existing jobs. The big question is: what sort of jobs?

According to the perceptual symbol hypothesis (Barsalou, 1999), word concepts trigger mental re-enactments of perceptual states and actions. While many studies have shown how word concepts modulate sensori-motor responses, it is less well known how sensori-motor actions influence access to word concepts in memory. Here, we investigated how well English words with strong horizontal or vertical associations are retrieved from memory dependent on how they are presented during encoding (i.e., horizontally or vertically printed). Initial pre-testing of 129 candidate words yielded 43 words with a strong horizontal association (e.g., floor, beach, border, etc.) and 51 words with a strong vertical association (e.g., tree, crane, bottle, etc.). These were quasi-randomly compiled into 160 'crossword arrays', each containing 5 horizontally and 5 vertically printed items drawn from the horizontal association word set, as well as 5 horizontally and 5 vertically printed items drawn from the vertical association word set.

We examine how wealth inequality and diversity in the perception of risk of a collective disaster impact cooperation levels in the context of a public goods game with uncertain and non-linear returns. In this game, individuals face a collective-risk dilemma where they may contribute or not to a common pool to reduce their chances of future losses. We draw our conclusions based on social simulations with populations of independent reinforcement learners with diverse levels of risk and wealth. We find that both wealth inequality and diversity in risk assessment can hinder cooperation and augment collective losses. Additionally, wealth inequality further exacerbates long term inequality, causing rich agents to become richer and poor agents to become poorer. On the other hand, diversity in risk only amplifies inequality when combined with bias in group assortment--i.e., high probability that agents from the same risk class play together. Our results also suggest that taking wealth inequality into account can help to design effective policies aiming at leveraging cooperation in large group sizes, a configuration where collective action is harder to achieve. Finally, we characterize the circumstances under which risk perception alignment is crucial and those under which reducing wealth inequality constitutes a deciding factor for collective welfare.

In The Feeling of Power, a story by celebrated American science fiction author Isaac Asimov, humanity has forgotten how to conduct even the simplest mathematical equations. In a distant future, complex machines conduct all operations, as men and women watch bewildered. Suddenly a man rediscovers pencil and paper arithmetic, empowering him to perform simple multiplications without relying on machine aid. Stunned by his new powers, he shares the discovery with Earth's government. The military establishment quickly seizes on the new powers to build a more effective, human-run space fleet to replace artificial intelligence and defeat Earth's enemy, planet Deneb.

A dress worn this week by Democratic Congresswoman Alexandria Ocasio-Cortez (D-NY), which bore the message "tax the rich," set off a wave of debate over how best to address wealth inequality, as Congress weighs a $3.5 trillion spending bill that includes tax hikes on corporations and high-earning individuals. The debate coincides with the ongoing pandemic in which billionaires, many of whom are tech company founders, have added $1.8 trillion in wealth while consumers have come to depend increasingly on services like e-commerce and teleconference, according to a report released last month by the Institute for Policy Studies. In a new interview, artificial intelligence expert Kai Fu-Lee -- who worked as an executive at Google (GOOG, GOOGL), Apple (AAPL), and Microsoft (MSFT) -- attributed the rise of wealth inequality in part to the tech boom in recent decades, predicting that the trend will worsen in coming years with the continued emergence of AI. "We can just already see all the internet companies," says Lee, the co-author of a new book entitled "AI 2041: Ten Visions for Our Future." "Without AI, they probably would be only worth half of what they're worth, because AI helped them monetize." "When it's simultaneously making a small number of people ultra-rich and making many people jobless," he says.

At the Last Futurist, we enjoy looking at AI Trends and digital transformation trends. In between those two are more broad technology trends. In fact these topics make up the mission statement of this new news site. However the last decade had a lot of technology and gadgets that didn't fare so well in the real world. The decade was mobile all the way, with mass adoption taking place the way we might expect the brain-computer interface (BCI) to achieve mass adoption in a future decade years from now. In the decade ahead the move to automated stores and electric vehicles are real trends, but it's important to differentiate the hype from the reality. Autonomous vehicles, quantum computing going mainstream, better self-learning AI, hang on a second! Even mass adoption of digital currencies is coming faster. From computers to the internet and smart phones, a few generations shows a lot of progress. But technology never stands still. Advertising has scaled a world of surveillance capitalism normalization and an AI-arms race is now taking place. Most technology trends and AI listicles only touch the surface of how humans are embedding technology increasingly into their lives. However looking at it from the perspectives of many industries and across technology and innovation stacks gives a more complete picture. The real world and customer experience are the real tests for new technological innovations and pivots. It will take decades for 3D printing, quantum computing and an AGI to even become mature, but an age of biotechnology and AI in healthcare, education and finance is inevitable. From Huawei, to ByteDance (TikTok), to Didi, China will wage major battles for global market share in 5G, consumer apps, E-commerce, mobile payments and ride sharing, among others. Chinese led tech companies -- with the support of the Chinese Government and venture funds such as Softbank Vision Fund -- can mean that in the 2020s China's ecosystem fully replaces Silicon Valley as the leader of innovation. In 2019, some believe this has already occurred.

Artificial intelligence is a tool humanity is wielding with increasing recklessness. We say it's for our common good with machine learning hype equal to business profits. But what happens when we don't have the code of ethics, laws, government accountability, corporate transparency and capability of monitoring the space to be able to achieve AI regulation? Artificial intelligence regulation isn't just complex terrain, it's uncharted territory for an age that is passing the baton from human leadership to machine learning emergence, automation, robotic manufacturing and deep learning reliance. Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans.

Elite dating apps are conspicuously widening the wealth gap in America, and everyone seems to be perfectly fine with it. Apps like the League, Tinder Select and Raya have become a convenient tool for rich singles to hook up with their fellow rich singles, leaving no room for people with measly income to join their privileged dating game. Bloomberg's Jeanna Smialek wrote Tuesday about how elite dating apps continue to worsen the wealth inequality in the U.S. due to their rules and regulations that cater only to the rich and the moneyed. One such app that Smialek tackled in her piece is the League, a social and dating mobile application that launched in 2015 and available only in select cities of the country. The League was intentionally made for those who are looking for love from people belonging to a high socioeconomic status.