- Title:
Biasedness In Artificial Intelligence
- Name:
George huang
- Company:
Irvine Valley College California USA 92618
- Abstract:
When it comes to artificial intelligence, we have to mention Turing, who is the beginning of artificial intelligence ,In 1948,Turing published a paper "Computing Machinery and Intelligence" on Mind,put forward The Imitation Game's theory,which we called “The Turing test”,based on this, from simple to complex,Artificial Intelligence (AI) has become more and more mature,and gotten rapidly evolved in recent years, becoming an integral part of various domains, from healthcare to autonomous vehicles and finance. This abstract provides a concise overview of the current landscape of AI, highlighting key advancements, challenges, and future prospects.The first section delves into the fundamental principles of AI, elucidating its core concepts such as machine learning, neural networks, and natural language processing. It elucidates how these techniques have revolutionised data analysis, enabling computers to learn from vast datasets and make predictions, decisions, and generate human-like language. Subsequently, the abstract explores the application of AI across various sectors. In Politics, AI may write a story or include information from various websites that may include biassed or unfactual information like parodies. The question is: How do we eliminate the biases and untruthful information when artificial intelligence collects this information and how do we humans acquire that information?The challenges associated with AI, including ethical concerns, bias in algorithms, and data privacy, are also discussed. Ensuring fairness and transparency in AI systems remains a paramount challenge, and addressing these issues is crucial for responsible AI deployment.
- Keyword:
Biasedness;Artificial Intelligence;fundamentals of AI;current issues;solutions
- DOI:
10.12250/jpciams2024090210
- Citation form:
George huang.Biasedness In Artificial Intelligence [J]. Computer Informatization and Mechanical System,2024,Vol.7,pp.44-47
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