Explainable AI (XAI), also known as artificial intelligence with explanations, is a type that uses AI to explain its decisions. This technology helps to mitigate ethical concerns, and builds trust between humans-machines. The question is: How can AI be made more understandable? The answer lies in the application and use cases for which explainable AI is desired. There are two possible applications for which explainable AI may be of value: self-driving and autonomous cars. This article will provide more details on the benefits of XAI.
XAI refers to a form of artificial Intelligence that gives explanations for the decisions it makes
XAI refers to a form of AI that has explanations for its decisions. This type of artificial intelligence is intended to make it easier for users to understand and predict the model's actions. It can identify bugs in code or components that could cause a model to fail. It can also help identify biases embedded in the training data. This article will briefly outline the main benefits and limitations of XAI.
It helps mitigate ethical challenges
There are growing privacy and ethical concerns about AI and data science. This is cause for concern. Companies can't rely on a single, consistent and robust method of assessing risk. Instead, they must find solutions quickly to solve the problem. Many companies confronting ethical problems at scale use ineffective policies that result in slow production and false positives in risk identification. Companies that collaborate with third parties to develop AI can exacerbate these problems.
It builds trust between humans, machines, and each other
Research has shown that explaining AI can help humans gain trust in the systems they use. This is significant because we draw conclusions about AI systems from three different factors: performance, working mechanisms and purpose. Beyond providing transparency about their purpose, explainable AI system provide metrics that can be used to measure them. These three elements are combined to improve trust between humans & machines. But they cannot do this on their own.
It is a method of machine to machine explainability
Explaining the reason behind a decision is crucial in an age of machine-to-machine communications and increasing automation to ensure that it has ethical and social benefits. The use of explainable AI has a variety of applications in manufacturing, from explaining problems on assembly lines to enhancing machine-to-machine communication and situational awareness between humans and machines. This method could also be helpful in military training. It can help mitigate some of those ethical issues that are often associated with AI.
It's relevant to telecommunications networks
The architecture of telecommunications system has fundamentally changed. This document describes the structure and relationships of the system's components. Cable and data networks used to coexist side-by-side, sharing the same technology and high speed digital pipes. In the 1960s, the Federal Communications Commission made the Carterphone decision, allowing consumers to purchase telecommunications services and products. It is possible that the first Internet-based VoIP service will be made available via a customer-owned WiFi area network.
FAQ
What is the current state of the AI sector?
The AI market is growing at an unparalleled rate. It's estimated that by 2020 there will be over 50 billion devices connected to the internet. This will mean that we will all have access to AI technology on our phones, tablets, and laptops.
Businesses will have to adjust to this change if they want to remain competitive. If they don't, they risk losing customers to companies that do.
You need to ask yourself, what business model would you use in order to capitalize on these opportunities? Do you envision a platform where users could upload their data? Then, connect it to other users. Or perhaps you would offer services such as image recognition or voice recognition?
No matter what your decision, it is important to consider how you might position yourself in relation to your competitors. Even though you might not win every time, you can still win big if all you do is play your cards well and keep innovating.
What are some examples AI-related applications?
AI is used in many areas, including finance, healthcare, manufacturing, transportation, energy, education, government, law enforcement, and defense. These are just a few of the many examples.
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Finance - AI can already detect fraud in banks. AI can identify suspicious activity by scanning millions of transactions daily.
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Healthcare - AI can be used to spot cancerous cells and diagnose diseases.
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Manufacturing – Artificial Intelligence is used in factories for efficiency improvements and cost reductions.
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Transportation - Self-driving vehicles have been successfully tested in California. They are currently being tested around the globe.
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Utilities are using AI to monitor power consumption patterns.
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Education - AI has been used for educational purposes. Students can communicate with robots through their smartphones, for instance.
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Government - Artificial Intelligence is used by governments to track criminals and terrorists as well as missing persons.
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Law Enforcement - AI is used in police investigations. Databases containing thousands hours of CCTV footage are available for detectives to search.
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Defense - AI is being used both offensively and defensively. In order to hack into enemy computer systems, AI systems could be used offensively. Artificial intelligence can also be used defensively to protect military bases from cyberattacks.
What does AI do?
An algorithm refers to a set of instructions that tells computers how to solve problems. An algorithm can be described as a sequence of steps. Each step has a condition that dictates when it should be executed. A computer executes each instructions sequentially until all conditions can be met. This repeats until the final outcome is reached.
For example, let's say you want to find the square root of 5. It is possible to write down every number between 1-10, calculate the square root for each and then take the average. This is not practical so you can instead write the following formula:
sqrt(x) x^0.5
This says to square the input, divide it by 2, then multiply by 0.5.
This is the same way a computer works. It takes the input and divides it. Then, it multiplies that number by 0.5. Finally, it outputs its answer.
AI is good or bad?
AI can be viewed both positively and negatively. The positive side is that AI makes it possible to complete tasks faster than ever. Programming programs that can perform word processing and spreadsheets is now much easier than ever. Instead, we can ask our computers to perform these functions.
People fear that AI may replace humans. Many believe that robots will eventually become smarter than their creators. They may even take over jobs.
What can AI be used for today?
Artificial intelligence (AI), which is also known as natural language processing, artificial agents, neural networks, expert system, etc., is an umbrella term. It's also known as smart machines.
Alan Turing created the first computer program in 1950. He was interested in whether computers could think. In his paper "Computing Machinery and Intelligence," he proposed a test for artificial intelligence. The test seeks to determine if a computer programme can communicate with a human.
In 1956, John McCarthy introduced the concept of artificial intelligence and coined the phrase "artificial intelligence" in his article "Artificial Intelligence."
Many AI-based technologies exist today. Some are easy to use and others more complicated. They can range from voice recognition software to self driving cars.
There are two main categories of AI: rule-based and statistical. Rule-based uses logic in order to make decisions. For example, a bank account balance would be calculated using rules like If there is $10 or more, withdraw $5; otherwise, deposit $1. Statistics are used to make decisions. A weather forecast might use historical data to predict the future.
Statistics
- In the first half of 2017, the company discovered and banned 300,000 terrorist-linked accounts, 95 percent of which were found by non-human, artificially intelligent machines. (builtin.com)
- In 2019, AI adoption among large companies increased by 47% compared to 2018, according to the latest Artificial IntelligenceIndex report. (marsner.com)
- By using BrainBox AI, commercial buildings can reduce total energy costs by 25% and improves occupant comfort by 60%. (analyticsinsight.net)
- According to the company's website, more than 800 financial firms use AlphaSense, including some Fortune 500 corporations. (builtin.com)
- Additionally, keeping in mind the current crisis, the AI is designed in a manner where it reduces the carbon footprint by 20-40%. (analyticsinsight.net)
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How To
How do I start using AI?
Artificial intelligence can be used to create algorithms that learn from their mistakes. The algorithm can then be improved upon by applying this learning.
If you want to add a feature where it suggests words that will complete a sentence, this could be done, for instance, when you write a text message. It would analyze your past messages to suggest similar phrases that you could choose from.
To make sure that the system understands what you want it to write, you will need to first train it.
Chatbots can also be created for answering your questions. One example is asking "What time does my flight leave?" The bot will reply that "the next one leaves around 8 am."
Our guide will show you how to get started in machine learning.