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LIMITATIONS OF AI

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LIMITATIONS OF AI

  1. 1. SANGHAMITRA SCHOOL Lesson -1 INTRDUCTION TO AI [ARTIFICIAL INTELLIGENCE]
  2. 2. HISTORY OF ARTIFICIAL INTELLIGENCE
  3. 3. LIMITATIONS OF ARTIFICIAL INTELLIGENCE With 90% of organizations taking a shot at artificial intelligence (AI) projects, enterprises are understanding the imperativeness of AI for effective business procedures. Burning through cash on AI projects could eventually chop down expenses on long-winded manual tasks individuals would need to conduct. This isn’t only a budgetary expense, yet a time cost, as tasks like data analysis and tracking, has been finished by human hand previously. Artificial intelligence conveys ease of access and promptness to data procedures unparalleled to earlier endeavors, which is the reason 96% of organizations said they hope to see machine learning projects keep on soaring in the next two years. While AI opens the new doors for some amazing prospects across different sectors, numerous usage challenges emerge. Beforehand, issues with AI execution have regularly been ascribed to employees’ lack of involvement with the innovation, bringing about an expectation to learn and adapt for business experts. Frequently, organizations need to go after outside talent to help get the most out of their assets. In any case, people are not exclusively to fault for AI’s limitations.
  4. 4. 1) Data Data utilization is one of the significant restrictions of Artificial Intelligence. For any program to begin, it requires data. It doesn’t make a difference if the program is in the training stage or moved to the execution phase, its desire for data never gets fulfilled. If you are hoping to implement AI into a program, the procedure goes like first, the software robots need some cognitive aptitudes to become more intelligent with time. There are likewise robots with cutting-edge cognitive aptitudes that utilize technologies like Machine Learning (ML), Optical Character Recognition (OCR), Natural Language Processing (NLP) and Robotic Process Automation (RPA) to extricate the significance of data restricted in the documents. From that point forward, different roles become possibly the most important factor like automating tasks that include critical thinking or decision making etc. Frequently, organizations believe they might not have enough data to work with AI in any case. The key here, however, is to recall that it’s not about having enough broad data, it’s about having “noteworthy data that will enable them to learn, that is appropriate for whatever task they have as a main priority,” emphasized David Parmenter, head of data science at Adobe. Another data-related confinement has to do with data benchmarks and guidelines. Organizations need to decide if the data has the correct parameters, said Whit Andrews, agenda manager for AI and distinguished analyst at Gartner. Companies need to ensure that their data can be imparted to various organizations dependent on government, state, and internal requirements for those companies, Andrews said.
  5. 5. 2) Cultural Limitations Put basically; this is about resistance to change. Individuals, usually noted, will, in general, be creatures of propensity; when we discover a strategy for completing a task that appears to take care of business viably and effectively, we like to stay with it. It frequently takes some influence before we will see that the disruption and cost that will definitely be brought about by changing methodology or embracing new procedures will be worth the all-around gains they will bring. This could be as easy as a reluctance towards what can be viewed as “giving over control”, regardless of whether that is specific to machines, or to the human employees who manage the technological framework that makes AI possible.
  6. 6. 3) Bias Shrouded bias is available in both individuals and data, and periodically bias is given over to data in light of people. We can’t carry out these responsibilities without getting data. At that point, you go out to shop around for data, and the data may have a bias in it that you don’t think about. You’re simply oblivious to it. One model is from the universe of autonomous cars. You will get more information in well off neighborhoods since that is the place autonomous vehicles are going to go first. The greatest thing organizations need to recollect while embracing AI is the reason, they need it. Try not to do AI for AI. Begin with a business case grounded in client insights from behavioral analytics and market surveying. Companies will end up squandering a great deal of time and cash trying to execute AI without any justifiable cause. Ensure your organization has the data and thinking first and then execute.
  7. 7. 4) Emotional Intelligence While AI is getting more astute step by step, we have achieved a point where computational power or speed is never again a constraint. It’s an ideal opportunity to work upon emotional intelligence of AI so it can communicate increasingly like Humans. Natural Language Processing (NLP) ought to be sufficiently effective to comprehend what the human is trying to state and his/her feelings behind it. In basic terms, the AI should comprehend the context of the discussion. The issue is AI lacks emotional intelligence as it cannot classify human sentiments and mindsets into one of a kind data points or profiles. In any case, things will start to change in the following couple of years.
  8. 8. 5) Shortage of Strategic Approach  Here and there, this is an amalgamation of a few different barriers– the absence of talent, the absence of the management buy-in, and a culture inadequately drenched in the points of interest and practicalities of AI and digital change. The outcome is frequently AI activities that aren’t planned at a strategic level, failure to address strategic business goals and don’t fit inside a company’s overall actions for development and business development.  Regularly the reason here is that, while organizations are comprehensively mindful of the significance of adopting AI innovation, and the favorable benefits it can offer, they fail to approach it from a strategic point of view; this implies completely understanding the points and goals of all aspects of AI operations, from data gathering to how the experiences revealed are imparted over the workforce and set to work. The answer to this one is quite direct, companies should always guarantee that an unmistakable procedure is set up before time and cash are spent on taking off costly and resource-intensive AI initiatives and pilots with no reasonable comprehension of the advantages they can bring.
  9. 9. ADVANTAGES OF ARTIFICIAL INTELLIGENCE 1) Reduction in Human Error: The phrase “human error” was born because humans make mistakes from time to time. Computers, however, do not make these mistakes if they are programmed properly. With Artificial intelligence, the decisions are taken from the previously gathered information applying a certain set of algorithms. So errors are reduced and the chance of reaching accuracy with a greater degree of precision is a possibility. Example: In Weather Forecasting using AI they have reduced the majority of human error.
  10. 10. 2) Takes risks instead of Humans: This is one of the biggest advantages of Artificial intelligence. We can overcome many risky limitations of humans by developing an AI Robot which in turn can do the risky things for us. Let it be going to mars, defuse a bomb, explore the deepest parts of oceans, mining for coal and oil, it can be used effectively in any kind of natural or man-made disasters.  Example: Have you heard about the Chernobyl nuclear power plant explosion in Ukraine? At that time there were no AI-powered robots that can help us to minimize the effect of radiation by controlling the fire in early stages, as any human went close to the core was dead in a matter of minutes. They eventually poured sand and boron from helicopters from a mere distance. AI Robots can be used in such situations where intervention can be hazardous.
  11. 11. 3) Available 24x7: An Average human will work for 4–6 hours a day excluding the breaks. Humans are built in such a way to get some time out for refreshing themselves and get ready for a new day of work and they even have weekly offed to stay intact with their work-life and personal life. But using AI we can make machines work 24x7 without any breaks and they don’t even get bored, unlike humans.  Example: Educational Institutes and Helpline centers are getting many queries and issues which can be handled effectively using AI.
  12. 12. 4) Helping in Repetitive Jobs: In our day-to-day work, we will be performing many repetitive works like sending a thanking mail, verifying certain documents for errors and many more things.Using artificial intelligence we can productively automate these mundane tasks and can even remove “boring” tasks for humans and free them up to be increasingly creative.  Example: In banks, we often see many verifications of documents to get a loan which is a repetitive task for the owner of the bank. Using AI Cognitive Automation the owner can speed up the process of verifying the documents by which both the customers and the owner will be benefited.
  13. 13. 5) Digital Assistance: Some of the highly advanced organizations use digital assistants to interact with users which saves the need for human resources. The digital assistants also used in many websites to provide things that users want. We can chat with them about what we are looking for. Some chatbots are designed in such a way that it’s become hard to determine that we’re chatting with a chatbot or a human being.  Example: We all know that organizations have a customer support team that needs to clarify the doubts and queries of the customers. Using AI the organizations can set up a Voice bot or Chatbot which can help customers with all their queries. We can see many organizations already started using them on their websites and mobile applications.
  14. 14. DISADVANTAGES OF ARTIFICIAL INTELLIGENCE 1) High Costs of Creation: As AI is updating every day the hardware and software need to get updated with time to meet the latest requirements. Machines need repairing and maintenance which need plenty of costs. It’ s creation requires huge costs as they are very complex machines. 2) Making Humans Lazy: AI is making humans lazy with its applications automating the majority of the work. Humans tend to get addicted to these inventions which can cause a problem to future generations.
  15. 15. 3) Unemployment: As AI is replacing the majority of the repetitive tasks and other works with robots,human interference is becoming less which will cause a major problem in the employment standards. Every organization is looking to replace the minimum qualified individuals with AI robots which can do similar work with more efficiency. 4) No Emotions: There is no doubt that machines are much better when it comes to working efficiently but they cannot replace the human connection that makes the team. Machines cannot develop a bond with humans which is an essential attribute when comes to Team Management. 5) Lacking Out of Box Thinking: Machines can perform only those tasks which they are designed or programmed to do, anything out of that they tend to crash or give irrelevant outputs which could be a
  16. 16. Done by : Sri Sai Aditya .K Class : 8th Section : D Roll Number : 26

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