When we speak about Artificial Intelligence, there are many questions that come to mind;
Is AI being used responsibly? Or are the results that AI produces even accurate? Can the result be explained?
AI is now widely used in everyday life and by millions of people, so these questions are being asked even more frequently.
Explainable AI (XAI) is a type of artificial technology in which humans can trust and understand the decisions made by the AI algorithms. XAI aims to give humans an understanding of the deep learning process involved in the technology, helping users to understand how the machine got the answer it did. Deep learning is a process that teaches computers to process the data given in a way that is similar to a human brain. XAI can improve the overall user experience by helping the end user trust that AI is making accurate decisions.
When it comes to the continuously evolving nature of AI, there are still improvements which must be considered in order to ensure that more and more people adopt the technology. Read below to see what we think these are.
Increased demand for transparency
There is a growing demand for AI systems to be transparent particularly in industries where the consequences of AI-powered decisions can be significant. With the use of XAI, these concerns should be even more transparent as users are able to see the "thought process" behind the AI technology and how it came to the decision it did. The clarity of this process will become more and more important ashumans will seek outproof that the models have been thoroughly tested.
Development of Explainable AI techniques
As the demand for Explainable AI increases, the technology must develop to meet the needs of the companies that are using them. These developments are likely to include feature attribution, model-agnostic interpretation, and counterfactual explanation.
Regulation and compliance
As AI becomes more ingrainedinto everyday society, there will be a stronger need for regulatory frameworks and compliance standards to ensure transparency and accountability of AI systems. There are currently three main topics for AI laws and regulations:
- Privacy and safety issues
- Responsibility and accountability
- The governance of autonomous intelligent systems.
Without strict regulations, AI is vulnerable and susceptible to hacking and producing incorrect data. These are just a couple of the risks that AI could cause when strict regulations are not put in place.
As AI continues to become a part of our daily lives, people will begin to have an increased focus on the ethics that surround the technology. Ethical considerations such as privacy fears, concerns that AI could replace human jobs, and the use of AI to deceive or manipulate other users.
Overall, as we continue to see an increase in AI’s presence into our society and day to day lives, the increased need for transparency and ethical practices must be considered so that everyone can use AI safely and efficiently.
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