6 Positive AI Visions for Future Work World

6 Positive AI Visions for Future Work World

You may know that the power of thinking develops in human beings alone, it does not require any kind of extraterrestrial power. Suppose, seeing something, hearing something, touching something, we think about how we should treat that thing; Is that so? This is the power of thinking. However, in the case of robots, they cannot create this power alone. The science behind building such intelligence inside robots is called artificial intelligence (Artificial Intelligence).

Artificial Intelligence (AI) is a big issue. Scientists from all over the world are constantly researching this subject.

You may have seen an example of artificial intelligence. Suppose, for example, that you have seen the movie Robot, which is based primarily on this artificial intelligence.

This technology is mainly used on computer systems. To do this, you have to go through three processes. This is - firstly learning which means that machines are taught what they have to do and what rules to follow to do those tasks, secondly, Reasoning means that they are the machines to move towards the right result. The rules were made to follow the instructions so that they could reach a certain result.

If we talk about the Particular Application of AI, then it includes expert systems, speech recognition, and machine vision. AI or Artificial Intelligence is a technology that can think like a human being and the way a human learns from any problem through his brain, then processes it, decides what should be done, and finally does it.

In this type of artificial intelligence, the machine has been given all the features of the human brain so that it can perform the work better.

If the current trend in AI is not significant then nothing. Day after day, we hear stories of systems and machines carrying things that, until very recently, we saw as the exclusive and permanent preservation of mankind: diagnosing medicine, drafting legal documents, designing buildings, and even composing music.

Our concern here, however, is with something more interesting: the possibility of high-level machine intelligence systems that surpass people in almost every task. This is not science fiction. In a recent survey, estimates among top computer scientists suggest a 50% chance that the technology will arrive in 45 years.

Importantly, that survey also expressed considerable disagreement. Some see high-level machine intelligence coming too fast, others too slow, if at all. Such views differ from those of popular literature in recent analyzes on the future of AI.

Yet despite these conflicting opinions, one thing is clear: if we think that such an outcome is possible, it should demand our attention. Continuing advances in these technologies could have dramatically disruptive effects - it would exacerbate recent trends in inequality, weaken the work as a force for social integration, and undermine the source of purpose and fulfillment for many.

Experts gather to share their AI visions

In April 2020, an ambitious initiative called Positive AI Economic Future was launched by Stuart Russell and Charles-Edward Boy, both members of the Global AI Council (GAIC) of the World Economic Forum. In a series of workshops and interviews, more than 150 experts from a variety of backgrounds came together to discuss these challenges, as well as potentially positive artificial intelligence perspectives and their implications for policymakers.

They included Madeleine Ashby (author of science fiction and expertise in strategic foresight), Ken Liu (author of the Hugo Award-winning science fiction and fantasy), and economists Darren Acemoglu (MIT) and Anna Salomons (Utrecht). The following is a summary of the conversation that ensued in the Forum's Positive AI Economic Future Report.

What will constitute 'work' in a future

Participants were divided on this question. One camp thought that freed from the shackles of traditional work, people could be engaged in exploring their new freedom, self-improvement, volunteering, or whatever else they considered satisfactory. Proponents of her case have been working to make the actual transcript of this statement available online.

The second camp of our workshops and interviews believed the opposite: traditional work may still be essential. To them, UBI is a confession of failure - it assumes that most people will have nothing of economic value to contribute to society. They can be fed, placed, and entertained - mostly by machine - but otherwise left to their own devices.

People will be engaged in providing interpersonal services that can be provided - or that we like to provide - only by humans. These include therapy, tutoring, life coaching, and community-building. That is, if we can no longer provide regular physical labor and regular mental labor, we can still provide our humanity. To create real value in such jobs, we need to be better at being human - a field where our education system and scientific research base are infamously weak.

So, while we think that the completion of traditional work would be a good thing or a bad thing, it seems that we need a radical redistribution of education and science in order to equip people to live a full life or to support a high-based economy. Value-added interpersonal service. We also need to ensure that the economic benefits of AI-enabled automation are fairly distributed to society

6 AI situations that could create a positive future

One of the biggest obstacles to action is that, at present, there is no consensus on what the future holds, perhaps because there is very little discussion about what might be desired. This lack of vision is a problem because, when it comes to high-level machine intelligence, we can quickly overwhelm ourselves with unprecedented technological change and irresistible economic power. This would be a huge opportunity.

For this reason, workshop participants and interview participants, from science-fiction writers to economists and AI experts, tried to express a positive outlook on the future where artificial intelligence could do most of what we now call work.

This scenario represents a potential trajectory for humanity. Although none of them are unequivocally achievable or desirable. And while there are elements of important agreement and consensus within the vision, there are often conflicts.

1. Human-centered artificial intelligence

Maybe you have a question in your mind, what is human-centered AI?

Human-centered AI learns from human input and collaboration, focusing on existing algorithms within a larger, human-based system. Human-centered AI is defined by systems that are constantly improving due to human input and provide an effective experience between humans and robots. Through the development of machine intelligence aimed at understanding human language, emotions, and behavior, human-centered AI pushes the boundaries of previously limited artificial intelligence solutions to bridge the gap between machines and humans.

From a business perspective, human-centric AI solutions provide a deeper understanding of the needs, aspirations, and drivers that drive customer behavior in your market with the help of human science and qualitatively thick data. Advanced contextual analyzes combine data and anthropology to provide specific behavioral information. When the analysis is applied to human behavior and preferences, patterns appear. These contextual analyzes combine data and anthropology to create dramatically improved, personalized customer experiences. Clear, informed business strategies can be created when companies know exactly what their customers do and expect

Society has decided to oppose excessive automation. Business leaders, computer scientists, and policymakers choose to develop technologies that increase rather than decrease the demand for workers. Incentives for the development of human-centered artificial intelligence will be strengthened and, if necessary, taxed on automation.

2. Shared economic prosperity

Today's political and economic structure is marked by globalization and the exponential expansion of AI automation. Their progress ensures development and prosperity - which is often not evenly distributed among countries. One study found that middle-income households in the U.S. declined while their productivity increased, making distribution problems more visible. Why is this digital age unbalancing the key drivers growing up in the union? A possible explanation through variables as an indicator of total factor productivity and globalization is presented in this article. Human capital investment, in the form of education, is discussed.

The economic benefits of technological advancement are widely shared worldwide. The scale of the global economy has expanded tenfold because artificial intelligence has greatly increased productivity. By sharing this prosperity, mankind can do more and achieve more. This approach can be achieved through a variety of interventions, from introducing a global tax system to improving unemployment insurance.

3. Flexible labor market

People’s creativity and hands-on support give people time to find new roles. People adapt to technological changes and find work in newly created professions. The policies will focus on improving educational and retraining opportunities as well as strengthening the social safety net for those who would otherwise be harmed by automation.

The rapid advancement of artificial intelligence (AI) and automation technology has the potential to significantly disrupt the labor market. Although AI and automation can increase the productivity of some employees, they can replace the work done by others and will probably transform almost all professions to some extent. In times of increasing economic inequality, increasing automation is occurring, raising the risk of widespread technological unemployment, and a new call for policy efforts to address the consequences of technological change.

 In this research paper, we discuss the barriers that prevent scientists from measuring the impact of AI and automation on the future of work. These barriers include the lack of high-quality data on the nature of the work (e.g., the dynamic requirements of the profession), and the lack of empirically informed models of basic micro-level processes (e.g., skill replacement and human-machine complementarity), and inadequate. Understanding how cognitive technologies interact with larger economic dynamics and institutional processes (e.g., urban migration and international trade policy). Overcoming these barriers requires refinement of data in the workplace efficiency as well as improvement of data longitude and spatial resolution. 

These improvements will enable multidisciplinary research to quantitatively monitor and predict complex evolution working with technological advances. Finally, in light of the fundamental uncertainties in predicting technological change, we suggest creating a decision framework that focuses on general balanced behavior as well as resilience in unforeseen situations.

4. Reunited company

Big companies focus on developing AI that benefits humanity and they do so without leaving too much economic or political power. This can be followed by changing corporate ownership structures and updating distrust policies.

Artificial intelligence is reshaping the business, although many are not in the blink of an eye. True, AI is now guiding decisions on everything from harvesting to bank loans, and the prospects of once fully automated customer service are skyrocketing. Technologies that enable AI, such as development platforms, huge processing power, and data storage, are advancing rapidly and becoming increasingly affordable. Companies' AI seems appropriate when it comes to capitalization. In fact, we estimate that AI will add $ 13 trillion to the global economy in the next decade.

 5. Civic empowerment and human development

In a world where there is less need to work and basic needs are met by UBI, meaningful unpaid activity brings increasing well-being. People may be engaged in the exploration, self-improvement, volunteering, or whatever else they deem satisfactory. Wider social engagement will be supported.

The purpose of this report is to start a broad discussion on what kind of future we want and the challenges we will have to face to achieve it. If technological advancement continues its relentless advancement, then the world will look very different for our children and grandchildren. These questions require more debate, research, and policy engagement - these are things we need to ignore now.

6. Fulfilling jobs

New jobs are more fulfilling than ever. Machines handle unsafe and tedious tasks, while people move on to more productive, fulfilling, and flexible jobs with greater human interaction. Achieving this includes strengthening labor organizations and increasing employee engagement on corporate boards.



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