Why MACHINE LEARNING and ARTIFICIAL INTELLIGENCE
“Growing up in the golden age of technology, I have witnessed how technological advancements have shaped our lives, from allowing physically challenged people to run, to catalysing medical breakthroughs; Technology has truly changed what it means to be human”. This line from my statement of purpose ‘SOP’ more than ever emphasizes the importance of AI and Machine Learning.
According to Stanford Researcher, John McCarthy, “Artificial Intelligence is the science and engineering of making intelligent machines, especially intelligent computer programs. Artificial Intelligence is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to biologically observable methods.”
Artificial intelligence and machine learning are helping people and businesses achieve key goals, obtain actionable insights, drive critical decisions, and create exciting, new, and innovative products and services. Businesses are migrating into AI and ML-enabled systems due to its promise of bringing advancement in respective industries. The changes are bound to happen in multiple sectors due to ML and AI’s capability of transforming the current work inertia. Despite its widespread lack of familiarity, AI is a technology that is transforming every walk of life. It is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decisionmaking. Two important breakthroughs led to the emergence of Machine Learning as the vehicle which is driving AI development forward with the speed it currently has. One of these was the realization — credited to Arthur Samuel in 1959 — that rather than teaching computers everything they need to know about the world and how to carry out tasks, it might be possible to teach them to learn for themselves. According to Bernard Marr , the second, more recently, was the emergence of the internet, and the huge increase in the amount of digital information being generated, stored, and made available for analysis.
Once these innovations were in place, engineers realized that rather than teaching computers and machines how to do everything, it would be far more efficient to code them to think like human beings, and then plug them into the internet to give them access to all of the information in the world. The demand for data scientist in the field artificial intelligence and machine learning is set to further rise 27.9% by 2026 according to The U.S Bureau of Labor Statistics. AI is not a futuristic vision, but rather something that is here today and being integrated with and deployed into a variety of sectors. This includes fields such as finance, national security, health care, criminal justice, transportation, and smart cities. There are numerous examples where AI already is making an impact on the world and augmenting human capabilities in significant ways
💊 Impacts of AI and Machine Learning on Medicine
Artificial intelligence is already making strides in detecting undiagnosed disease. In December of last year, a team of researchers at Google trained a deep neural network to detect diabetic retinopathy with higher accuracy than an ophthalmologist. Machine Learning — particularly Deep Learning algorithms — have recently made huge advances in automatically diagnosing diseases, making diagnostics cheaper and more accessible.
Machine Learning algorithms can learn to see patterns similarly to the way doctors see them. A key difference is that algorithms need a lot of concrete examples — many thousands — in order to learn. Since there is plenty of good data available in these cases, algorithms are becoming just as good at diagnostics as the experts. Time is the most valuable resource in healthcare. Medical response delayed by a few minutes could mean death for a patient suffering with a heart stroke. Even for terminally-ill patients, an early diagnosis means a few more days to spend with friends and family. AI makes this happen.The difference is: the algorithm can draw conclusions in a fraction of a second, and it can be reproduced inexpensively all over the world. Soon everyone, everywhere could have access to the same quality of top expert in radiology diagnostics, and for a low price. AI can analyze large amounts of historical data to tease out novel insights that can predict the future course of a person’s health. AI is the key to providing personalized healthcare that incorporates many types of personal data.
Data amassed from a person’s genomics, their medical record, and even their smartwatch can alert the person and their doctor to medical risks and hopefully someday predict their long-term outlook. On the practitioners’ side, AI can also cut lengthy processes significantly, allowing them to focus on providing the best care possible. Deep learning models can turn a process like sifting through medical documents and test records into a one-click insight with the help of a single program.
AI and Machine Learning on Business
According to Chanakya Kyatham, you visit Amazon, search for an iPad, review the product feature, and get lost in your daily routine. Later that day, you visit Facebook and find ads on the same iPad model. You start seeing that product everywhere. AI and ML are making these recommendations to you. These technologies are helping advertisers personalize their marketing approach. AI will continue to transform the e-commerce space, help marketers personalize their marketing approach, and save a lot of money for business owners. Machine Learning-enabled technologies have been implemented in detecting frauds and tracking suspicious behaviors in businesses. As AI and ML learn over time, apps and software can self-adjust and act accordingly to defend vulnerable systems.
Artificial intelligence and machine learning are also changing how businesses interact with their customers. We’re already seeing feature-rich customer relationship management systems such as Zoho and Salesforce. Customer service will remain an essential part of all businesses, irrespective of size and industry type. And ML is expected to completely modify customer service or support in the coming years. The AI-enabled systems are also expected to have sentiment analysis technology that will significantly help in responding to customer concerns.
Impacts of AI and Machine Learning on Agriculture
The global population is expected to reach more than nine billion by 2050 which will require an increase in agricultural production by 70% to fulfill the demand. Scientists have proffered a smarter approach to increase efficiency in how we farm by the effective use of productive data analytics and artificial intelligence.
Gone are the days of a farmer working their land with hand tools, artificial intelligence now allows farmers to improve their efficiency and reduce their environmental impact. With data analytics fused with powerful ML(Machine learning) & DL(Deep Learning) concepts as well as the increase in computational power, agricultural efficiency has become more viable, even for smallholder farmers. In September 2018, a coalition launched a project that will run through 2030 and look at data from approximately 500 million farmers in impoverished areas from 50 countries.
AI and machine learning are improving and yielding more advantages for the agricultural sector by Managing Crop Diseases and Pests, Making Yield Predictions and Improve Crop Management, Improving Agricultural Supply Chain Management and Creating Better Investment Opportunities. In a paper I wrote; linked above, detailed explanations and the tools, softwares and technology exploited for this advancement are provided.
Impacts of AI and Machine Learning on Education
Global adoption of technology in education is transforming the way we teach and learn. Artificial Intelligence is one of the disruptive techniques to customize the experience of different learning groups, teachers, and tutors. Artificial Intelligence helps find out what a student does and does not know, building a personalized study schedule for each learner considering the knowledge gaps. In such a way, AI tailors studies according to student’s specific needs, increasing their efficiency.
To do it, many companies train their AIs, armed by the Knowledge Space Theory, to define and represent the knowledge gaps, taking into account the complexity of scientific concepts relations between each other (one can stimulate the learning of another or become a basis for filling in the gap).This is what it look like;
AI also helps generate and update the content of the lessons, keeping the information up to date and customizing it for different learning curves. The adoption of innovative AI technologies opens up new ways of interacting for students with learning disabilities. AI grants access to education for all kinds of students; deaf and hard of hearing, visually impaired, people with ASD.
AI and Machine Learning Impacting Finance
Investments in financial AI in the United States tripled between 2013 and 2014 to a total of $12.2 billion. According to observers in that sector, “Decisions about loans are now being made by software that can take into account a variety of finely parsed data about a borrower, rather than just a credit score and a background check. A prominent example of this is taking place in stock exchanges, where high-frequency trading by machines has replaced much of human decisionmaking. People submit buy and sell orders, and computers match them in the blink of an eye without human intervention. Machines can spot trading inefficiencies or market differentials on a very small scale and execute trades that make money according to investor instructions.
Fraud detection represents another way AI is helpful in financial systems. It sometimes is difficult to discern fraudulent activities in large organizations, but AI can identify abnormalities, outliers, or deviant cases requiring additional investigation. That helps managers find problems early in the cycle, before they reach dangerous levels.
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The above outlined sectors are a few of the real and true strengths of ARTIFICIAL INTELLIGENCE and MACHINE LEARNING. Transportation, National Security, Legal systems and Green Energy are other sectors that AI has been exploited for globalization and developement in 1st and some 2nd and 3rd world countries. Smart cities like Cincinnati and a number of metropolitan areas are adopting applications that use AI to improve service delivery, environmental planning, resource management, energy utilization, and crime prevention, among other things. Seattle, for example, has embraced sustainability and is using AI to manage energy usage and resource management. These developmental strides are only possible because of proper access to data.
According to a McKinsey Global Institute study, nations that promote open data sources and data sharing are the ones most likely to see AI advances. In this regard, the United States has a substantial advantage over China. Global ratings on data openness show that U.S. ranks eighth overall in the world, compared to 93 for China. It is important to note that — The world is on the cusp of revolutionizing many sectors through artificial intelligence, but the way AI systems are developed need to be better understood for proper management and planning to strategize development.
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References
- Artificial intelligence in healthcare: past, present and future Jiang F, Jiang Y, Zhi H, et al Artificial intelligence in healthcare: past, present and future Stroke and Vascular Neurology 2017; 2:doi: 10.1136/svn-2017–000101
- Dominic Barton, Jonathan Woetzel, Jeongmin Seong, and Qinzheng Tian, “Artificial Intelligence: Implications for China” (New York: McKinsey Global Institute, April 2017), p. 1.
- Roles of AI in education Lisa Plitnichenko, https://elearningindustry.com/ai-is-changing-the-education-industry-5-ways
- Shubhendu and Vijay, “Applicability of Artificial Intelligence in Different Fields of Life.”
- Why Is AI & ML Important and How Will It Impact Business? Chanakya Kyatham