In this scenario, consider FarmLogs, a farming management app presently used by many farmers in the US, which uses technology and data to help farmers track the weather, monitor fields, obtain insights into soil utilizing historical satellite imagery, and even identify irregular plant growth. Real-time data analytics<\/strong> <\/em><\/a>help farmers to maximize their crop yields and thus, in turn, their profits too.<\/span><\/p>\n

1.5- Strengthened economy<\/em><\/strong><\/h4>\n

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Probably<\/em> all of us have seen headlines that state something like adoption of AI<\/strong> will lead to unemployment. In reality, this is far from the truth. Artificial intelligence<\/strong> promotes a gradual evolution in the job field, which will be positive with the companies planning ahead.<\/p>\n

Humans will still work, but they\u2019ll be working more efficiently with the help of AI<\/strong>.<\/span> Besides this unparalleled combination of machine and human, there will be a natural requirement of trained people who\u2019ll be supervising the systems, apart from those who\u2019ll actually do certain jobs. It\u2019ll gradually result into more job openings, thus solidifying the economy.<\/p>\n

1.6- Smart cities<\/em><\/strong><\/h4>\n

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AI<\/strong><\/em> is being implemented by various authorities to optimize different facilities. Artificial intelligence<\/strong> is considered as a way to deal with large volumes of data and to identify efficient ways of responding to various public requests. Instead of addressing service issues in ad hoc manners, authorities are implementing AI<\/strong> to be proactive in how urban services can be provided.<\/p>\n

Smart city applications often use artificial intelligence<\/strong> to improve environmental planning, service delivery, energy utilization, resource management, and crime prevention, among others. Some of the top applications include intelligent traffic signals, e-governance applications, smart meters for utilities, Wi-Fi kiosks etc.<\/p>\n

1.7- Overall lifestyle<\/em><\/strong><\/h4>\n

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With<\/em> the increasing implementation of AI<\/strong> in different segments of society, overall lifestyle of the humans gets enhanced. Some of the mundane tasks such as data entry or answering emails can be performed by intelligent assistants, freeing up precious time for humans to focus on creative aspects of the work.<\/p>\n

Smart homes<\/strong><\/em><\/a> can be made capable of providing better security and reducing energy usage that would greatly promote the concept of a greener environment.<\/p>\n

2- Steps we should take<\/em><\/strong><\/h3>\n

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With<\/em> all the AI benefits<\/em><\/strong><\/a>, there comes some significant disadvantages as well, but that\u2019s natural for any technology.<\/span><\/p>\n

The question that is making lots of people worried is this: With too much of authority given to the machines, how can implementation of AI<\/strong> be made more favorable to the society? Or, at the least, how to make it not act like a threat to human life and property?<\/p>\n

2.1- Transparency is the key<\/em><\/strong><\/h4>\n

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Results<\/em> can be questioned even with a greatly planned decision-making system, if the reasoning can\u2019t be demonstrated. For example, if AI<\/strong> has diagnosed an illness, the patient can always ask for a proper reasoning, failing which would lead to non-transparency of the system.<\/p>\n

Assuming that artificial intelligence<\/strong> will be making hugely important decisions, implementation of AI<\/strong> has to be perfectly planned and the results have to be transparent and explainable to be accepted by the society. In addition, AI should be use data science<\/strong><\/em><\/a> to improve the living conditions.<\/p>\n

2.2- Importance of AI curriculum<\/em><\/strong><\/h4>\n

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Artificial intelligence<\/strong><\/em> should be used where it\u2019s more effective and efficient to employ a machine to handle the task compared to engaging a human brain to perform it.<\/span> So, companies should ensure scenarios where success gets replicated in raising the technology, in terms of both costs and resources.<\/p>\n

High-quality protocols should also be developed by data scientists<\/em><\/strong><\/a> when it comes to selecting training data and taxonomies for AI<\/strong>. If it\u2019s trained with patchy, skewed or flawed examples, the results will be going to be unreliable. So, it also needs to be ensured that the data is relevant, appropriate, accurate, diverse, accurately labeled, and representative.<\/p>\n

For instance, if an AI<\/strong>-enabled system for hiring recommendations is trained on the data of present and past employees solely, and those employees aren\u2019t diverse (e.g. predominantly older white females), the resulting model would likely be biased unfairly against candidates who\u2019re young, racial minorities, and male. Even after an AI<\/strong>-enabled system is launched, the risk and quality of unfair bias need to be assessed by human overseers in ongoing new training data.<\/p>\n

In addition, as we aim to improve the fairness and efficacy of AI<\/strong> with proper training data to benefit the society, we should also keep in mind that fundamental privacy principles are closely related to the massive amounts of data used by AI<\/strong>. Usage and retention of personal data needs to be minimized, while limiting the ways in which that data could be used in the future. Big data analytics solutions<\/strong><\/em><\/a> include the remedy of these problems.<\/p>\n

Final takeaways<\/em><\/strong><\/h3>\n

It\u2019s<\/em> important to note that AI<\/strong> isn\u2019t able to learn on its own and thus, humans are required to help any type of artificial intelligence<\/strong> obtain a better understanding of all types of jobs, processes, things etc. When it comes to maximizing societal benefits, perhaps the best approach to leverage both AI<\/strong> systems and human-only systems is to do what each of them does best. Leveraging artificial intelligence<\/strong> as well as the best of human ability and values promises greater progress in accountability, transparency, and fairness. And this will be playing a crucial role in building a strong trust for AI<\/strong> in the society.<\/p>\n

For instance, AI<\/strong> can be put to work to do the time-consuming analysis of the huge amount of information available. Building a culture of continuous learning and collaboration is crucial to take maximum advantage of artificial intelligence<\/strong>.<\/span> This combined approach is what will make processes and people even more important than they are today. And to make the most out of the technology, society needs to deploy AI<\/strong> that puts humans first, protects human rights, and fosters humans\u2019 trust. Immersive data science<\/strong> experience<\/strong><\/em><\/a> is proof that we can rely on artificial intelligence.<\/strong><\/p>\n