Statement of the Problem:
Artificial Intelligence (AI) has become a buzzword in the field of education, promising to revolutionize the way we teach and learn. Artificial Intelligence refers to the ability of machines to perform tasks that typically require human intelligence, such as learning, reasoning, and problem-solving. In recent years, artificial intelligence has been increasingly used in education to personalize learning, improve assessment and feedback, and streamline administrative tasks. However, there are also concerns about the negative effects of artificial intelligence on education, such as bias and discrimination, dependence on technology, job loss for educators, and decreased social interaction. This paper aims to provide an overview of both the positive and negative effects of artificial intelligence in education and explore ways to balance them.
Identification of Issue:
Does artificial intelligence have the potential to positively and negatively impact our educational systems, from personalizing learning and improving assessment and feedback to creating bias, job loss for educators, and decreased social interaction?
Overview:
Artificial Intelligence is a rapidly advancing technology that has the potential to revolutionize education. While some argue that artificial intelligence can enhance teaching and learning outcomes, others raise concerns about its impact on student privacy, equity, and teacher roles.
Those in favor of artificial intelligence integration argue that it can provide personalized learning experiences for students, improve teacher effectiveness by automating administrative tasks, and increase access to education through virtual learning environments. Additionally, proponents believe that artificial intelligence can help address the achievement gap by providing customized interventions for struggling students.
On the other hand, those against artificial intelligence use in education are concerned about issues such as data privacy and security, algorithmic bias and discrimination, lack of transparency in decision-making processes, and the potential for job displacement among teachers. They also question whether artificial intelligence can truly replace human interaction and social-emotional learning.
Assumptions:
Artificial Intelligence can potentially be used to help identify the most effective teaching methods based on students’ contexts and learning background. It can automate monotonous operational tasks, generate assessments and automate grading and feedback. Artificial Intelligence does not only impact what students learn through recommendations, but also how they learn, what are the learning gaps, which pedagogies are more effective and how to retain learner’s attention (Chaudhry & Kazim, 2021, p. 157). Vincent-Lancrin and Vlies (2020) suggest that artificial intelligence in education can be used to accelerate personalized learning, support students with special needs, and predict and assess new skillsets. Luckin et al., (2016) suggest that in order for artificial intelligence in education to be successful, we need intelligent technologies that embody what we know about great teaching and learning, and which are then used effectively in real-life settings. Goksel and Bozkurt (2019) suggests that the current state of artificial intelligence in education is suitable for adaptive learning, personalization and learning styles, expert systems and intelligent tutoring systems. Mijwil et al., (2022) suggest that artificial intelligence is the future of education since it is has demonstrated consistent growth and yields great benefit to learners.
Arguments For:
The potential of artificial intelligence (AI) to transform teaching and learning has become increasingly exciting as the field of education evolves and adapts to the changing needs of students and society. Studies have supported the following conclusions:
- AI applications can identify pedagogical materials and approaches adapted to the level of individual students, and make predictions, recommendations, and decisions about the next steps of the learning process based on data from individual students ("Trustworthy artificial intelligence (AI) in education," 2020, p. 7).
- Automatic correction of learners’ answers, and this service saves time and effort by eliminating a large number of papers (Hwang et al., 2020, p. 103).
- Artificial Intelligence has the tools and techniques to conduct the fine-grained analysis that allows us to track each learner’s development of skills and capabilities as they interact and learn over time. This tracking of individual learners can then be collated and interpreted as required to provide knowledge about progress at the school, district, and country level (Luckin et al., 2016, p. 34).
- Using artificial intelligence, we can collect data about which teaching and learning methods work best. This information to track how well learners are doing with different types of teaching modalities. This can help create a catalog of the best teaching practices that fit the skills people need in the 21st century across a variety of environments (Luckin et al., 2016, p. 34).
- AI can help visually impaired students to read books and recognize faces, and thus to learn and socialize within their communities. Specialized systems have been designed to assist students with all kinds of disabilities. Powered by AI, technologies such as augmented and virtual reality (AR/VR) and robotics support the learning and engagement of students with health impairments and mental health issues ("Trustworthy artificial intelligence (AI) in education," 2020, p. 8).
- Intelligent tutoring systems (ITSs) are one of the innovative applications that reflects the advantages of artificial intelligence in educational platform. ITSs use computer-based learning environments to assist students in learning, practicing, or mastering new abilities by giving them tailored teaching based on how proficient they are with a particular topic or skill set ("What are the advantages and disadvantages of AI in education?," 2021).
Arguments Against:
There has been growing opposition to the integration of artificial intelligence in education, with critics raising concerns about its impact on the quality and effectiveness of learning and use of data.
- There would be a huge communication gap between teachers and students if robots were used as part-time instructors during school hours rather than people because they couldn't interact socially with each other as people could ("What are the advantages and disadvantages of AI in education?," 2021).
- The integration of AI in education has a significant downside - the lack of interaction with human counterparts during class hinders students from honing their social skills ("What are the advantages and disadvantages of AI in education?," 2021).
- While smart machines improve the education experience, they should not be considered a substitute for personal interaction. Relying too much on these machines to grade or tutor may lead to educational oversights that hurt learners more than help (LiveTiles, 2021).
- Artificial intelligence has the potential to become addictive. Students could lose interest in learning because they are more interested in AI devices, which is a disadvantage of artificial intelligence use for education purposes (ULLAH, 2022).
- It reduces kids' ability to think critically and increases their reliance on technology rather than teaching them how to complete tasks independently ("What are the advantages and disadvantages of AI in education?," 2021).
- AI should respect the rule of law, human rights and democratic values, throughout the AI system lifecycle. These include freedom, dignity and autonomy, privacy and data protection, non-discrimination and equality, diversity, fairness, social justice, and internationally recognized labor rights ("Trustworthy artificial intelligence (AI) in education," 2020, p. 13).
Analysis of the Validity of Arguments
The advantages of utilizing artificial intelligence in education are abundant and far-reaching. Personalized learning can be accelerated through the application of AI, while students with distinct requirements may receive assistance from this technology to reduce dropout rates. It is also possible for skillsets to be evaluated more efficiently and accurately using AI-driven assessment protocols. Additionally, it contributes significantly towards developing abilities that have low risks of becoming automated such as creative thinking or higher cognitive skills like innovation. In addition, grading systems could benefit tremendously from implementing Artificial Intelligence; personalized feedbacks by teachers would become easier than ever before once again utilizing these cutting-edge technologies which eventually leads you into a world beyond your imagination with immersive experiences coming alive right in front of them inside classrooms.
School dropout is a major educational policy issue across the globe – although countries
with different levels of affluence may focus on different ages of dropout. In low-income
countries, 60% of upper secondary school-age children were out of school in 2015. In 2018,
completion rates for primary, lower secondary, and upper secondary education were 68%, 44%
and 21%, respectively, far from the objective of universal completion by 2030 ("Trustworthy artificial intelligence (AI) in education," 2020, p. 11). Dropout rates could also decrease thanks to predictive analysis from student performance and behavior data processed via an inspired use of artificial intelligence systems; interventions created based on risk identification keep at-risk candidates motivated towards reaching academic goals set before them.
The challenges of implementing trustworthy AI in education include creating and maintaining trust in AI systems, ensuring transparency, explainability, and accountability of AI systems, protecting and securing (personal) data, lack of evidence about the effectiveness of many AI solutions in education, uncertainty about whether current promising AI applications are technically trustworthy, possibility of non-trustworthy behaviors by some actors in the education sector, cost of buying technology must be matched by tangible benefits, education systems rarely have establishments that allow for implementation of AI, ensuring that AI systems are secure and private, ensuring that AI systems are transparent and explainable, ensuring that AI systems are fair and unbiased, and ensuring that AI systems are accountable and auditable.
Too often, failures are not identified until after they have had real-world effects on learners and teachers and long-term contracts have already been signed. Even more concerning than monetary costs, are the data rents being paid in the form of learner and teacher data (Komljenovic, 2021, p. 324). When students and staff interact with digital platforms, they leave digital traces behind. Content can include posts and discussions in the virtual learning environment; metadata can include user locations, device data, time spent on specific sites, and click-throughs. Metadata and content can both be regarded as personal information, which may be identifiable or non-identifiable. Data such as this is captured and valued by platforms in the digital economy. Data rentiership refers to the ‘pursuit of innovation strategies designed to capture or extract value through ownership and control of data as an asset’ (Birch et al., 2020, p. 3).
Finally, Machine Language (ML), which is used in increasing numbers of AI in education tools, generates its outputs is often unknown even to the developers (Rudin 2019). Due to their technical complexity and proprietary nature, Machine Language systems are neither transparent nor understandable. Any “explanation must be tailored to the context and provided in a manner that is useful and comprehensible for an individual, allowing individuals to effectively protect their rights” (Leslie et al., 2021, p.15). Having a clear understanding of how ML works allows users to make informed decisions and act accordingly in order to ensure their rights are protected.
Values Emphasized and Compromised
Those who favor AI in education are excited about the potential benefits that AI can bring to the field. These benefits include personalized learning, support for students with special needs, predictive analysis to reduce dropout rates, and assessing new skillsets. AI can also help achieve global educational targets by promoting inclusive and equitable quality education and lifelong learning opportunities for all. Additionally, AI has the potential to augment human capabilities and enhance creativity, advance inclusion of underrepresented populations, reduce economic, social, gender and other inequalities, and protect natural environments.
Opponents of AI in education have put forward several valid concerns. For example, AI could possibly diminish quality teaching, inadvertently or otherwise, by attempting to replace human methods of instruction. Additionally, existing biases in online systems like facial recognition technology could be perpetuated in classrooms if AI algorithms are not carefully calibrated to ensure that all students receive equitable treatment. Furthermore, student data privacy is highly sensitive and should be taken into account when considering any adoption of this technology; robust privacy legislation must be enacted and enforced before schools even consider putting AI into actual use. Lastly, both cost-effectiveness and job displacement among teachers must also be accounted for when debating whether or not AI has a place in the classroom - these two elements alone could make or break such implementations depending on how they impact individual classrooms and districts.
Personal Position
Although some are skeptical, I acknowledge the enthusiasm regarding AI's potential advantages for education. Personalized learning and specialized support for pupils with disabilities as well as anticipatory evaluations keeping students from quitting school represent just a few ways in which AI technology can improve educational experiences. Furthermore, improper handling of environmental problems may be reduced by using Artificial Intelligence to reduce inequalities that prevent broad inclusion within schools among other strategies.
As I reflect on the topic of AI in education, it becomes apparent that there are those who have expressed legitimate apprehensions. The notion is plausible that if artificial intelligence supersedes human instruction methods entirely, instructional quality could suffer as a result. Moreover, facial recognition technologies and other algorithmic systems may sustain biases which cause untoward consequences for pupils within their learning environments. Beyond this point still remains an additional caveat - one must contemplate student data privacy before integrating any form of AI into educational settings; comprehensive legislation regarding these types of affairs ought to be instituted without delay so all sensitive information will remain well-guarded against potential breaches or misuse down the line.
When discussing whether AI should be introduced into schools, it is vital to also consider the monetary feasibility and possible effects on employment among educators. It's critical that we account for these factors since they can have noteworthy consequences for specific institutions or regions.
After taking these factors into account, I have a tendency to be careful about employing AI in education. Although the possible advantages are important, we must also thoroughly consider and confront potential risks and worries. We need to verify that AI is used responsibly and ethically while being thoughtfully inserted strategically into educational methods. The ultimate objective ought to be achieving equilibrium between benefits versus drawbacks of deploying AI in education so students enjoy an optimal learning experience as their rights in regards privacy remain secure.
Suggestions for Problem Solutions
There exist a multitude of strategies that can be implemented to harmonize the utilization of AI in education while taking into account both its possible advantages and disadvantages.
- Enforce Ethical and Reliable Practices: During the development and usage of AI applications, prioritizing favorable results for society as well as environmental sustainability are important. This encompass protecting students' confidentiality with regards to personal information alongside securing data integrity across all interfaces; additionally, guaranteeing that algorithms do not propagate preexisting cultural prejudices or systematic injustices should also remain at utmost importance.
- Teacher Support: Human teachers and AI technology could become powerful collaborators within the educational system, working together to create a learning environment of unprecedented quality. By incorporating both human expertise and cutting-edge artificial intelligence into teaching, we can unlock exciting new possibilities for students everywhere.
- Involve Stakeholders: It is crucial to engage all parties with vested interests in AI's application within the educational sector. From educators and students, policymakers, parents to industry experts; each voice should be heard when developing ethical guidelines that govern its use. Through this collaborative effort aimed at creating a framework of best practices for AI integration in education settings, we can better exploit its potential benefits while mitigating any inherent risks associated with it.
References
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Goksel, N., & Bozkurt, A. (2019). Artificial intelligence in education. Handbook of Research on Learning in the Age of Transhumanism, 224-236. https://doi.org/10.4018/978-1-5225-8431-5.ch014
Hwang, G., Xie, H., Wah, B. W., & Gašević, D. (2020). Vision, challenges, roles and research issues of artificial intelligence in education. Computers and Education: Artificial Intelligence, 1, 100001. https://doi.org/10.1016/j.caeai.2020.100001
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Leslie, D., Burr, C., Aitken, M., Cowls, J., Katell, M., & Briggs, M. (2021). Artificial intelligence, human rights, democracy, and the rule of law: A primer. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3817999
LiveTiles. (2021, February 5). 15 pros and 6 cons of artificial intelligence in the classroom. https://livetilesglobal.com/pros-cons-artificial-intelligence-classroom/
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence Unleased: An Argument for AI in Education.
Mijwil, M. M., Aggarwal, K., Mutar, D. S., Mansour, N., & Singh, R. S. (2022). The position of artificial intelligence in the future of education: An overview. Asian Journal of Applied Sciences, 10(2). https://doi.org/10.24203/ajas.v10i2.6956
Rudin, C. (2019). Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature Machine Intelligence, 1(5), 206-215. https://doi.org/10.1038/s42256-019-0048-x
Trustworthy artificial intelligence (AI) in education. (2020). OECD Education Working Papers. https://doi.org/10.1787/a6c90fa9-en
ULLAH, R. (2022, October 24). Advantages and disadvantages of artificial intelligence in education. Tech Baji. https://techbaji.com/education/advantages-disadvantages-artificial-intelligence-education/
What are the advantages and disadvantages of AI in education? (2021, June 22). Careerera.com. https://www.careerera.com/blog/advantages-and-disadvantages-of-ai-in-education#:~:text=One%20of%20the%20drawbacks%20of%20artificial%20intelligence%20(AI)%20in%20education,each%20student%2C%20fewer%20people%20are
