1)What is Artifical intelligence
The term computing was coined in 1956, however AI has become a lot of widespread nowadays due to knowledge volumes, advanced algorithms, and enhancements in computing power and storage.
Early AI analysis within the fifties explored topics like problem solving and symbolic ways. within the sixties, the United States of America Department of Defense took interest in this sort of work and commenced coaching computers to mimic basic human reasoning. as an example, the Defense Advanced analysis comes Agency (DARPA) completed street mapping comes within the nineteen Seventies. DARPA created intelligent personal assistants in 2003, long before Siri, Alexa or Cortana were home names.
2) Impact of A.I on social media
Expanding Social Networks Through Recommendation Engines
Recommendation engines, that utilize machine learning to filter info supported user preferences, contribute to the creation of this customized list. once you interact with social media accounts and posts, the advice engine learns from your past activity, so interprets patterns in your knowledge to predict a listing of accounts that you simply might probably act with.
Eye-Catching User Recommendations
The recommendation engines collect data on the content you engage with, from pinning a picture on Pinterest to commenting on an Instagram post, and then they display the material that they anticipate you will enjoy.
Sentiment Analysis
Sentiment analysis uses linguistic communicationprocess (NLP) to spot positive and negative words in posts and comments on social media. With this info, businesses will systematically, quickly, and accurately reply to client complaints.
Facial recognition
“As computing evolves, it magnifies the power to use personal info in ways in which will come in privacy interests by raising analysis of non-public info to new levels of power and speed.” biometric authentication systems provide a preview of the privacy problems that emerge. biometric authentication systems area units being deployed in cities and airports around America. However, China’s use of biometric authentication as a tool of authoritarian management in Xinjiang et al have woke up opposition to the current growth and concerns a ban on the utilization of biometric authentication.
Conclusion
Towards accountable AI
In certain high-risk sectors such as health and finance, various sector-specific legal protections and guidelines for products and services exist. However, the simple applicability of these laws to AI-based decision-making processes may not be appropriate. For specific aspects of algorithmic decisions, new legal protections may be needed. For example, while no anti-discrimination law directly regulates decision-making by AI, the extant laws are equally silent about the means of decision-making that they do govern41. Therefore, it will fall within the jurisdiction of anti-discrimination legislation to regulate decisions arrived at through the use of AI as well, particularly when the decision-making AI is being used by an entity having constitutional or legal obligations to be unbiased. review of AI ethics principles and guidelines will need to be done on an ongoing basis given the rapid pace of development of this emerging technology
Currently, India does not have an overarching guidance framework for the use of AI systems. Establishing such a framework would be crucial for providing guidance to various stakeholders in the responsible management of Artificial Intelligence in India.
Reference
1)https://sitn.hms.harvard.edu/flash/2017/history-artificial-intelligence/
2)https://www.analyticsinsight.net/artificial-intelligence-growth-and-development-in-india/
3)https://www.niti.gov.in/sites/default/files/2021-02/Responsible-AI-22022021.pdf
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