By VICTOR ANJOS
But those who interact with AI will develop empathy for AI systems. They will understand how these systems work and recognize how AI can be of value to a business.
One way you can help people feel more confident in using AI is to train them to understand how an AI system works and how they can teach AI to operate. The AI setup becomes more accessible for people to manage when they know how it works and sees what they can do with the setup. People will be even more confident when they notice how their input can directly influence how well AI can learn things.
tl;dr Give me the Goods
The User Has Full Control
One way to teach people about AI is to help them understand how an AI development program works. While an AI program can learn many things, it works best when an outside party has some control over the work.
For example, a user can create a chatbot through a unique computer program. The human can use this program to prepare many things for a chatbot:
- The websites where the chatbot can operate;
- The messages people will receive when opening a chatbot;
- Any unique responses that will appear based on questionnaire responses or other terms people enter;
- An answer tree where individual options are available based on keywords and other terms; the tree can be as thorough as necessary;
- How well the chatbot can collect user data, including what types of data it can gather from users.
The AI can learn through the interactions it has with other people. But the user is responsible for getting the communications ready the first time around. The user’s input will guide the AI into finding the right answers or improving how well it can handle data.
Users can adjust the answer tree and responses as necessary. New programming rules can also allow the AI to work with synonyms, context terms, and other factors.
Machine Learning Is Easy to Adjust
Another way to help teach AI to people is to help them see how machine learning works and how it can be easy to adjust as necessary. Machine learning is about helping predict outcomes in various situations. TechTarget reports that machine learning involves using historical data to figure out what might work.
Machine learning can include support for handling unique opportunities for work. New criteria can help analyze how groups can share data.
Relying Less on Rules and Logic
The journal Science writes that in the past, AI programs have relied on rules and logic to dictate results and operations. Today’s AI programs work with a few programmed rules that humans create. While there are some rules to follow, the AI will not generalize data. It uses multiple standards for understanding how to make decisions.
One idea that people can use when teaching AI is to use probabilistic programming languages or PPLs. Cornell University says PPLs are about combining rigid code structures in AI with probability considerations. The AI will review prior data and content and use it to determine the probability of someone requesting a specific material.
PPLs involve using statistical models that identify what can work at a time. A PPL helps find the most likely answer to a problem and uses it to create more positive results. The language reminds the AI that the rules for something can always change. While rules and logic can help, these aren’t going to be critical for every situation.
Training Metadata
The next aspect of AI to explore involves the use of metadata. People can review the metadata they gather from documents and other content and use it to refine the AI further. The AI can read the documents and use the metadata to dictate future responses to many questions.
InfuseAI writes that metadata is data that describes other pieces of data. Metadata helps review content based on what people search for and creates new ways for the AI to interact with others.
AI can use metadata in many ways:
- The AI can extract the data from whatever documents or reports a person inputs.
- The data is analyzed and modeled based on unique parameters the AI will use. The AI can use many terms to determine what metadata is necessary for work.
- All data is traced to find connections between different items. The function helps the AI link responses together.
- The AI can also record its performance and review how well it can respond to queries and responses based on different terms.
The functionality of AI makes it easier for people to handle the content.
Monitoring Is Critical
People can also teach AI by understanding how to monitor AI and provide feedback to the program as necessary. Monitoring allows humans to see how artificial intelligence operates and if people are receiving the support they request from an AI platform.
KPMG reports that diagnostic assessments of AI can review how well a program works based on keyword usage, how it completes tasks, and user feedback. You can analyze factors like what functions AI uses when making decisions and what biases the program holds. Users can refine the AI further if they can review issues and find fixes for these problems.
Users can monitor the AI as often as necessary, but weekly reports are often ideal. A dashboard program can help see how well the AI works and if there are any changes necessary to the work at hand.
A Final Word
AI is simple for people to handle when they learn how it works. Teaching AI to people and explaining how it works and learns will be essential to helping them feel confident in what AI provides. More importantly, people can use what they learn to teach the AI themselves.
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