New Expectations for Artificial Intelligence

7/23/2020

New Expectations for AI. INTRO: | by venkat vajradhar | Medium

New Expectations for AI venkat vajradhar Oct 1, 2019 ¡ 3 min read

INTRO: The field of Artificial Intelligence (AI) encompasses a wide variety of technologies, from image recognition to robotics and autonomous vehicles, with potential benefits as well as their risks.

AI is generally defined as a technical category with the ability to provide advanced information processing skills. Given the infantile stages of this technology, it is not surprising that associated risks are also being slowly identified.

When it comes to analyzing the potential risks and risks of AI services due to intentional abuse or accidental system failures, it is beneficial to use a constructive perspective on its associated risks. The lack of a constructive perspective may lead to a limited problem and set of solutions as AI shapes both and its expanding environment.

To Know About: How Artificial Intelligence Will Change in 2050?

It is important to understand the difference between agency and structure when adopting a constructive perspective. While the abusive perspective focuses on changing the innate incentives, motivations, or accessibility of the malicious person, the risk perspective focuses on developing the skills or attention of the engineer.

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7/23/2020

New Expectations for AI. INTRO: | by venkat vajradhar | Medium

Behavioral change involves two levels of focus on the individual agent. However, the constructivist view begins with the premise that the risk level does not change frequently, based on the example of avalanche even after the behavioral change of the individual agent, which may be prevented by asking for the cause of steepness rather than steepness. Asking for specific events that turn it off.

To change our way of thinking about the risks and dangers of AI, one of the main questions that need to be asked is whether there is pressure on decision-makers to see if they can change socio-economic or political structures. Make risky or expensive decisions, regardless of how well-intentioned or competent they are.

Such concern is most applicable to the security sector where a country’s missile, submarine and command, and control systems can be closely tracked by improving data and processing capabilities. Also, AI’s well-known ability to lead to monopoly markets due to the scale of revenue and labor displacement achieved by major tech companies is linked to issues related to structural mechanisms outside of security.

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As shown in these examples, the proliferation of AI can be detrimental to society, even if the misuse of technology does not occur. The negative consequences of AI arise from changes like the environment, which provides the background for interpersonal interaction.

Another question that needs to be asked to transform our psychology into constructive thinking is whether the socio-economic and political structures that address the dangers stemming from AI can be addressed as risks or abuses.

As a recent example, Uber’s fatal car accident associated with the AI system in early 2018 was thought to be due to its vision system, however, afterward, it became clear that the emergency brake had been deliberately stopped to prevent engineers from making them. The car looks bad with its highly sensitive braking system compared to other competitors. So, trading with security was under pressure from higher management to eliminate the model because market opportunities were low.

The lesson to be drawn from this event is that rather than focusing on technical issues, one must also consider the nature of the incentives in a particular system.

While the increase in the number and capabilities of engineers may help somewhat, it does not alleviate the problem unless the structural stress associated with both internal https://medium.com/@pvvajradhar/new-expectations-for-ai-cf93ad1d6260

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7/23/2020

New Expectations for AI. INTRO: | by venkat vajradhar | Medium

(such as employee career concerns) and external factors (such as market conditions) is altered.

In other words, technological changes and investments are insufficient to mitigate security risks. Constructive interventions can be done at a simpler level by regulatory entities such as courts or legislatures so that all stakeholders have an understanding of the respective responsibilities. To accomplish this, it is not necessary that some resources and capacity should be available in regulatory bodies.

Closing Point: Given the rapid proliferation of technology in our daily lives, it is difficult to assess both the potential risks and benefits of AI technology. However, the constructivist perspective opens new avenues for thinking about the risks and dangers of AI along with other technologies.

P.VenkatVajradhar Author

Arti cial Intelligence

AI

Machine Learning

Neural Networks

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