The potential of using artificial intelligence in education to enhance learning, assist teachers and fuel more effective individualized learning is exciting, but also a bit daunting. To even have an intelligent conversation about AI in education, one must first push past imaginary science-fiction scenarios of computers and robots teaching our children, replacing teachers and reducing the human element from what is a fundamentally human activity.
Automating administrative tasks is also one of five potential benefits spotlighted by Bernard Marr, an author, futurist and technology advisor who cites figures forecasting 47.5% growth from 2017-2021 in the use of artificial intelligence in education in the U.S.
Artificial Intelligence is Really Useful in Education Sector
There is also considerable optimism around the idea that, as artificial intelligence becomes a more integral part of the classroom, teachers will be better equipped to offer an individualized learning experience for every student.
Table of ContentsI. Qualities of artificial intelligenceII. Applications in diverse sectorsIII. Policy, regulatory, and ethical issuesIV. RecommendationsV. Conclusion
Most people are not very familiar with the concept of artificial intelligence (AI). As an illustration, when 1,500 senior business leaders in the United States in 2017 were asked about AI, only 17 percent said they were familiar with it.1 A number of them were not sure what it was or how it would affect their particular companies. They understood there was considerable potential for altering business processes, but were not clear how AI could be deployed within their own organizations.
The United States should develop a data strategy that promotes innovation and consumer protection. Right now, there are no uniform standards in terms of data access, data sharing, or data protection. Almost all the data are proprietary in nature and not shared very broadly with the research community, and this limits innovation and system design. AI requires data to test and improve its learning capacity.50 Without structured and unstructured data sets, it will be nearly impossible to gain the full benefits of artificial intelligence.
According to Greg Brockman, the co-founder of OpenAI, the U.S. federal government invests only $1.1 billion in non-classified AI technology.55 That is far lower than the amount being spent by China or other leading nations in this area of research. That shortfall is noteworthy because the economic payoffs of AI are substantial. In order to boost economic development and social innovation, federal officials need to increase investment in artificial intelligence and data analytics. Higher investment is likely to pay for itself many times over in economic and social benefits.56
As AI applications accelerate across many sectors, it is vital that we reimagine our educational institutions for a world where AI will be ubiquitous and students need a different kind of training than they currently receive. Right now, many students do not receive instruction in the kinds of skills that will be needed in an AI-dominated landscape. For example, there currently are shortages of data scientists, computer scientists, engineers, coders, and platform developers. These are skills that are in short supply; unless our educational system generates more people with these capabilities, it will limit AI development.
Federal officials need to think about how they deal with artificial intelligence. As noted previously, there are many issues ranging from the need for improved data access to addressing issues of bias and discrimination. It is vital that these and other concerns be considered so we gain the full benefits of this emerging technology.
If interpreted stringently, these rules will make it difficult for European software designers (and American designers who work with European counterparts) to incorporate artificial intelligence and high-definition mapping in autonomous vehicles. Central to navigation in these cars and trucks is tracking location and movements. Without high-definition maps containing geo-coded data and the deep learning that makes use of this information, fully autonomous driving will stagnate in Europe. Through this and other data protection actions, the European Union is putting its manufacturers and software designers at a significant disadvantage to the rest of the world.
Bias and discrimination are serious issues for AI. There already have been a number of cases of unfair treatment linked to historic data, and steps need to be undertaken to make sure that does not become prevalent in artificial intelligence. Existing statutes governing discrimination in the physical economy need to be extended to digital platforms. That will help protect consumers and build confidence in these systems as a whole.
To summarize, the world is on the cusp of revolutionizing many sectors through artificial intelligence and data analytics. There already are significant deployments in finance, national security, health care, criminal justice, transportation, and smart cities that have altered decisionmaking, business models, risk mitigation, and system performance. These developments are generating substantial economic and social benefits.
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 due to the major implications these technologies will have for society as a whole.
Ask any parent who has struggled to help their teenager with algebra, and they will be very excited about the potential of AI to support their children when they are struggling at home with homework or test preparations. Tutoring and studying programs are becoming more advanced thanks to artificial intelligence, and soon they will be more available and able to respond to a range of learning styles.
There are many more AI applications for education that are being developed including AI mentors for learners, further development of smart content and a new method of personal development for educators through virtual global conferences. Education might be a bit slower to the adoption of artificial intelligence and machine learning, but the changes are beginning and will continue.
Although the education sector is the one most influenced by humans, Artificial Intelligence has slowly begun to seep its roots into the education sector as well. Even in the education sector, this slow transition of Artificial Intelligence has helped increase productivity among faculties and helped them concentrate more on students than office or administration work.
Artificial Intelligence finds diverse applications in the healthcare sector. AI applications are used in healthcare to build sophisticated machines that can detect diseases and identify cancer cells. Artificial Intelligence can help analyze chronic conditions with lab and other medical data to ensure early diagnosis. AI uses the combination of historical data and medical intelligence for the discovery of new drugs.
A new artificial intelligence system made by the company OpenAI called ChatGPT is raising eyebrows and concern for how the new generation of artificial intelligence is going to affect society. The new AI technology is surprising users by generating responses that seem incredibly intelligent on a myriad of subjects.
Machine learning is a subfield of artificial intelligence, which is broadly defined as the capability of a machine to imitate intelligent human behavior. Artificial intelligence systems are used to perform complex tasks in a way that is similar to how humans solve problems.
Ways to fight against bias in machine learning including carefully vetting training data and putting organizational support behind ethical artificial intelligence efforts, like making sure your organization embraces human-centered AI, the practice of seeking input from people of different backgrounds, experiences, and lifestyles when designing AI systems. Initiatives working on this issue include the Algorithmic Justice League and The Moral Machine project.
Machine Learning (ML) and Artificial Intelligence (AI) are key drivers of growth and innovation across all industries, and the education sector is no different. According to eLearning Industry, upwards of 47% of learning management tools will be enabled with AI capabilities in the next three years.
While AI-powered solutions have been in the EdTech space for some time, the industry has been slow to adopt them. However, the pandemic drastically shifted the landscape, forcing educators to rely on technology for virtual learning. Now, 86% of educators say technology should be a core part of education. AI has the power to optimize both learning and teaching, helping the education sector evolve to better benefit students and teachers alike.
However, educational technology has its challenges, particularly when it comes to implementation and use. For example, despite growing interest in the use of AR, artificial intelligence, and other emerging technology, less than 10 percent of schools report having these tools in their classrooms, according to Project Tomorrow. Additional concerns include excessive screen time, the effectiveness of teachers using the technology, and worries about technology equity.
Teachers can leverage technology to achieve new levels of productivity, implement useful digital tools to expand learning opportunities for students, and increase student support and engagement. It also enables teachers to improve their instruction methods and personalize learning. Schools can benefit from technology by reducing the costs of physical instructional materials, enhancing educational program efficiency, and making the best use of teacher time.
A focus on nurturing unique human skills that artificial intelligence (AI) and machines seem unable to replicate: Many of these experts discussed in their responses the human talents they believe machines and automation may not be able to duplicate, noting that these should be the skills developed and nurtured by education and training programs to prepare people to work successfully alongside AI. These respondents suggest that workers of the future will learn to deeply cultivate and exploit creativity, collaborative activity, abstract and systems thinking, complex communication, and the ability to thrive in diverse environments. 2ff7e9595c
Comments