Explainable AI (XAI), also known as artificial intelligence with explanations, is a type that uses AI to explain its decisions. This technology can help reduce ethical concerns as well as build trust between humans & machines. But the question remains: What can be done to make AI more understandable? It all comes down to the specific application and use cases where explainable AI is needed. Explainable AI is valuable in two areas: autonomous vehicles and self-driving car. In this article, we will examine the potential benefits of XAI in a more detailed way.
XAI, a type of artificial intelligence that provides explanations for its actions, is called XAI.
XAI refers to a form of AI that has explanations for its decisions. This form of artificial intelligence is designed to make it easier to understand the model's steps and predictions. It can help to detect bugs in code and parts that may affect a model's performance. It can help detect biases in the training data. This article will briefly review the main benefits of XAI.
It helps mitigate ethical challenges
It is concerning to see the increasing privacy and ethical concerns regarding AI and data sciences. Companies are forced to look for solutions in an attempt to avoid problems. Most companies dealing with ethical issues at scale have ineffective policies and procedures which lead to inefficient risk identification and slow production. These problems are further exacerbated when companies work in collaboration with third parties on AI development.
It enhances trust between humans & machines
Researchers discovered that explaining AI increases trust in the systems used by humans. This is crucial because we infer about AI systems based upon three different bases: performance and working mechanisms. Explainable AI systems, in addition to providing metrics for testing, also provide transparency about the system's purpose. These three elements are combined to improve trust between humans & machines. They cannot do it alone.
It is a method of machine to machine explainability
It is important to explain why a decision was made in today's world of increased automation and machine–to–machine communication. This will help ensure ethical and sustainable social benefits. There are many applications for explainable AI in manufacturing. They can help solve problems on assembly lines or improve machine-tomachine communication. 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 is relevant to telecommunications systems
The architecture of telecommunications systems has changed fundamentally. It describes the system's overall structure and the relationships it has with its components. Cable and data networks existed side by side before, sharing the same technology platform and high-speed digital pipe. In 1960, the Federal Communications Commission issued the Carterphone decision allowing consumers to purchase telecommunications service and products. An individual customer might be able to access the first Internet-based VoIP system through their WiFi local network.
FAQ
What is the latest AI invention
The latest AI invention is called "Deep Learning." Deep learning is an artificial Intelligence technique that makes use of neural networks (a form of machine learning) in order to perform tasks such speech recognition, image recognition, and natural language process. Google developed it in 2012.
Google is the most recent to apply deep learning in creating a computer program that could create its own code. This was accomplished using a neural network named "Google Brain," which was trained with a lot of data from YouTube videos.
This enabled the system learn to write its own programs.
IBM announced in 2015 the creation of a computer program which could create music. Music creation is also performed using neural networks. These networks are also known as NN-FM (neural networks to music).
How does AI work?
An algorithm is a sequence of instructions that instructs a computer to solve a problem. An algorithm can be expressed as a series of steps. Each step has a condition that determines when it should execute. Each instruction is executed sequentially by the computer until all conditions have been met. This is repeated until the final result can be achieved.
Let's say, for instance, you want to find 5. You could write down each number between 1-10 and calculate the square roots for each. Then, take the average. You could instead use the following formula to write down:
sqrt(x) x^0.5
This is how to square the input, then divide it by 2 and multiply by 0.5.
The same principle is followed by a computer. It takes your input, multiplies it with 0.5, divides it again, subtracts 1 then outputs the result.
AI is used for what?
Artificial intelligence, a field of computer science, deals with the simulation and manipulation of intelligent behavior in practical applications like robotics, natural language processing, gaming, and so on.
AI is also called machine learning. Machine learning is the study on how machines learn from their environment without any explicitly programmed rules.
Two main reasons AI is used are:
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To make your life easier.
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To be able to do things better than ourselves.
Self-driving automobiles are an excellent example. We don't need to pay someone else to drive us around anymore because we can use AI to do it instead.
What is AI used today?
Artificial intelligence (AI) is an umbrella term for machine learning, natural language processing, robotics, autonomous agents, neural networks, expert systems, etc. It's also known by the term smart machines.
Alan Turing created the first computer program in 1950. His interest was in computers' ability to think. In his paper "Computing Machinery and Intelligence," he proposed a test for artificial intelligence. The test tests whether a computer program can have a conversation with an actual human.
In 1956, John McCarthy introduced the concept of artificial intelligence and coined the phrase "artificial intelligence" in his article "Artificial Intelligence."
Today we have many different types of AI-based technologies. Some are simple and easy to use, while others are much harder to implement. These include voice recognition software and self-driving cars.
There are two major categories of AI: rule based and statistical. Rule-based uses logic for making decisions. For example, a bank balance would be calculated as follows: If it has $10 or more, withdraw $5. If it has less than $10, deposit $1. Statistics is the use of statistics to make decisions. For instance, a weather forecast might look at historical data to predict what will happen next.
How does AI work?
Basic computing principles are necessary to understand how AI works.
Computers store information in memory. Computers interpret coded programs to process information. The code tells computers what to do next.
An algorithm is a set or instructions that tells the computer how to accomplish a task. These algorithms are often written in code.
An algorithm is a recipe. A recipe might contain ingredients and steps. Each step might be an instruction. A step might be "add water to a pot" or "heat the pan until boiling."
What is the current status of the AI industry
The AI industry is growing at a remarkable rate. By 2020, there will be more than 50 billion connected devices to the internet. This will enable us to all access AI technology through our smartphones, 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.
It is up to you to decide what type of business model you would use in order take advantage of these potential opportunities. What if people uploaded their data to a platform and were able to connect with other users? Perhaps you could also offer services such a voice recognition or image recognition.
No matter what you do, think about how your position could be compared to others. Although you might not always win, if you are smart and continue to innovate, you could win big!
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)
- By using BrainBox AI, commercial buildings can reduce total energy costs by 25% and improves occupant comfort by 60%. (analyticsinsight.net)
- While all of it is still what seems like a far way off, the future of this technology presents a Catch-22, able to solve the world's problems and likely to power all the A.I. systems on earth, but also incredibly dangerous in the wrong hands. (forbes.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)
- That's as many of us that have been in that AI space would say, it's about 70 or 80 percent of the work. (finra.org)
External Links
How To
How to setup Alexa to talk when charging
Alexa is Amazon's virtual assistant. She can answer your questions, provide information and play music. It can even listen to you while you're sleeping -- all without your having to pick-up your phone.
Alexa can answer any question you may have. Just say "Alexa", followed up by a question. Alexa will respond instantly with clear, understandable spoken answers. Alexa will improve and learn over time. You can ask Alexa questions and receive new answers everytime.
You can also control other connected devices like lights, thermostats, locks, cameras, and more.
Alexa can adjust the temperature or turn off the lights.
Setting up Alexa to Talk While Charging
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Open Alexa App. Tap the Menu icon (). Tap Settings.
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Tap Advanced settings.
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Select Speech Recognition
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Select Yes, always listen.
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Select Yes, you will only hear the word "wake"
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Select Yes and use a microphone.
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Select No, do not use a mic.
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Step 2. Set Up Your Voice Profile.
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Select a name and describe what you want to say about your voice.
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Step 3. Step 3.
Use the command "Alexa" to get started.
Ex: Alexa, good morning!
Alexa will reply if she understands what you are asking. For example, "Good morning John Smith."
Alexa will not reply if she doesn’t understand your request.
Make these changes and restart your device if necessary.
Notice: If the speech recognition language is changed, the device may need to be restarted again.