Ever since Artificial Intelligence was introduced to the world, people have pointed out the lack of understanding of human emotions that these machines have. Through the article “Building machines that better understand human goals”, researchers have proposed the introduction of social awareness into AI systems. It is their opinion that if machines can comprehend a human’s imperfect reasoning, and make inferences based on that – then it would help the machines provide better assistance. The team’s model is based on Bayesian inference, which calculates the degree of belief in a hypothesis after evidence has been observed. AI would work out possibilities of the agent’s course of action, based on their beliefs and tendencies.
Sequential Inverse Plan Search
In the last decade, AI has made great progress from near-science fiction to common reality across a wide range of business applications. If AI can take into account human errors, misjudgments, and staggered planning, then it can deduce goals and provide solutions in a better way. As discussed in the article, people tend to make partial plans wherein they gradually move one step closer to the ultimate goal. The research team’s inference algorithm, called “Sequential Inverse Plan Search” does exactly this. It is important to note that machines nowadays operate on the assumption that humans work towards a goal with optimal dedication whereas, in reality, humans work sub-optimally to achieve their goals. A person is more likely to divide their ultimate goals into smaller goals, involving shorter steps – which provides much more clarity of thought but also increases the chance of making errors.
Benefits of AI Devices
An AI device with social intelligence would benefit us in terms of time management and mental clarity. Imagine if a machine can comprehend when you are likely to make an error in judgment, or when your partial plan may not eventually lead you to the desired goal. It should be enough for you to just falter, or achieve a smaller goal, for the machine to understand what you ultimately aim to achieve. Undoubtedly, if assisting devices can evaluate a human’s plan of action while considering mistakes they may make and short-sighted actions they may take, it will improve the quality of service that they provide.
Nature of the Brain and its Relation with the Mind
It’s been long since philosophers and scientists have been debating about the nature of the brain and its relation with the mind. The relevance of these questions shines, when the theme is stated as the possibility to build machines; will they be able to replicate human capabilities? You can find various uses of AI even in our daily lives. All our smart devices have artificial intelligence. You can buy various smart devices such as smartphones, smartwatches, smart speakers, etc. from alternatives to eBay at great deals and discounts.
Studies show that pairing people with computers is getting easier. Accurate computer vision and image processing software programs are getting more and more common. This is further causing the costs to drop for consumer systems that read brain activity. Working together also helps address concerns about the ethics and bias of algorithm decisions as well as legal questions about accountability. More detailed studies prove that humans are undeniably less accurate than AI. However, humans are much more confident about their choices than AI is.
Bottom Line
From these two facts, it can be inferred that combining the two factors offer a useful mix of accuracy as well as confidence. After all these discussions, the fact of the matter remains that machines and algorithms do not have to and in fact should not replace humans. What can be assumed as the best option is for them both to work with each other, to find the best of all outcomes.