Harvard Case - Ethics and AI: The 2020 International Baccalaureate Grading Scandal
"Ethics and AI: The 2020 International Baccalaureate Grading Scandal" Harvard business case study is written by Anton S. Ovchinnikov. It deals with the challenges in the field of Strategy. The case study is 12 page(s) long and it was first published on : Nov 15, 2020
At Fern Fort University, we recommend a comprehensive approach to address the ethical and technological challenges posed by the 2020 International Baccalaureate (IB) grading scandal. This approach involves a multi-pronged strategy focusing on transparency, accountability, and ethical AI development.
2. Background
The case study revolves around the IB's decision to utilize an AI-powered algorithm to grade students' exams in 2020 due to the COVID-19 pandemic. This decision, while intended to ensure fairness and consistency, resulted in significant controversy as the algorithm produced inaccurate and biased results, leading to widespread student dissatisfaction and calls for reform.
The main protagonists of the case are the IB, its stakeholders (students, teachers, parents, and universities), and the developers of the AI algorithm. The case highlights the complex ethical considerations surrounding the use of AI in high-stakes assessments, particularly in an international context.
3. Analysis of the Case Study
This case study can be analyzed through the lens of strategic planning, corporate governance, and ethical considerations in technology.
Strategic Planning: The IB's decision to implement AI-based grading was a strategic response to the unprecedented circumstances of the pandemic. However, the lack of thorough strategic planning and scenario planning led to a flawed implementation. The organization failed to adequately consider the potential risks and ethical implications of relying solely on an AI algorithm for such a critical process.
Corporate Governance: The IB's decision-making process lacked transparency and accountability. The lack of clear communication and involvement of stakeholders in the development and implementation of the AI system contributed to the public backlash. The IB's corporate governance structure needs to be strengthened to ensure greater transparency and stakeholder engagement in future decisions involving technology.
Ethical Considerations in Technology: The case highlights the ethical dilemmas surrounding the use of AI in education. The algorithm's bias and lack of transparency raise concerns about fairness and equity. The IB must prioritize ethical considerations in its future technological endeavors, ensuring that AI systems are developed and deployed responsibly and ethically.
Porter's Five Forces: The IB operates in a highly competitive environment. The use of AI for grading could be seen as a disruptive innovation, potentially impacting the competitive landscape of international education. However, the lack of transparency and ethical concerns associated with the IB's approach could weaken its competitive position.
Value Chain: The IB's value chain involves various stakeholders, including students, teachers, examiners, and universities. The AI-based grading system significantly impacted the value chain, leading to disruptions in the assessment process and eroding trust among stakeholders. The IB needs to re-evaluate its value chain and ensure that technology is integrated ethically and effectively.
4. Recommendations
To address the ethical and technological challenges highlighted in the case, the IB should implement the following recommendations:
Establish an Ethics Committee: Create a dedicated committee comprised of experts in ethics, education, and AI to oversee the development and deployment of AI systems within the IB. This committee should be responsible for establishing ethical guidelines, conducting risk assessments, and ensuring transparency in AI-related decisions.
Enhance Transparency and Accountability: The IB should commit to greater transparency in its use of AI. This includes publishing clear documentation of the algorithms used, their limitations, and the data used to train them. The IB should also implement robust mechanisms for auditing and monitoring AI systems to ensure accountability and prevent biases.
Develop a Comprehensive AI Strategy: The IB should develop a comprehensive strategy for integrating AI into its assessment processes. This strategy should prioritize ethical considerations, data privacy, and student well-being. It should also involve stakeholder engagement, including students, teachers, and universities, to ensure buy-in and address concerns.
Invest in AI Education and Training: The IB should invest in training and education programs for teachers, examiners, and students on the ethical use of AI in education. This will foster understanding and critical thinking skills related to AI technologies and promote responsible use.
Promote Collaboration and Partnerships: The IB should collaborate with leading AI researchers, ethicists, and educational institutions to develop ethical and robust AI systems for assessment. This collaboration will leverage expertise and ensure that the IB's approach aligns with best practices in the field.
5. Basis of Recommendations
These recommendations are based on the following considerations:
Core Competencies and Consistency with Mission: The IB's core competencies include academic excellence, internationalism, and inclusivity. These recommendations align with the IB's mission by promoting ethical and equitable use of technology in education.
External Customers and Internal Clients: The recommendations address the concerns of external customers (students, universities) and internal clients (teachers, examiners) by promoting transparency, accountability, and ethical AI development.
Competitors: The recommendations help the IB maintain its competitive edge by addressing the ethical and technological challenges posed by the use of AI in education. This will strengthen the IB's reputation and build trust among stakeholders.
Attractiveness ' Quantitative Measures: While quantifying the impact of these recommendations is challenging, the potential benefits include improved student satisfaction, increased trust in the IB, and a stronger reputation for ethical AI practices.
6. Conclusion
The 2020 IB grading scandal highlights the critical need for ethical considerations in the development and deployment of AI systems, particularly in education. By implementing the recommendations outlined above, the IB can address the ethical and technological challenges posed by the scandal, restore trust among stakeholders, and ensure a more equitable and transparent assessment system.
7. Discussion
Alternative approaches to addressing the scandal could include:
- Abandoning AI-based grading altogether: This would address ethical concerns but may not be feasible in the long term.
- Developing a hybrid approach: Combining human judgment with AI-based tools could offer a more balanced solution.
The risks associated with the recommendations include:
- Resistance to change: Some stakeholders may resist the implementation of new ethical guidelines and AI practices.
- Cost of implementation: Implementing the recommendations will require significant resources and investment.
Key assumptions include:
- Commitment from the IB leadership: The recommendations require strong commitment from the IB's leadership to prioritize ethical AI development and implement the necessary changes.
- Availability of expertise: The IB will need to recruit or partner with experts in ethics, AI, and education to implement the recommendations effectively.
8. Next Steps
The IB should prioritize the following steps to implement the recommendations:
- Establish the Ethics Committee within the next 6 months.
- Develop a comprehensive AI strategy within the next 12 months.
- Implement training programs for teachers and examiners within the next 18 months.
- Collaborate with external partners to develop ethical AI systems within the next 24 months.
By taking these steps, the IB can move towards a future where AI is used ethically and responsibly to enhance education and promote equity for all students.
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Case Description
The world's first truly global AI crisis came at a time when no one expected. In the summer of 2020, after college exams were cancelled due to COVID-19 restrictions, tens of thousands of students received nonsensical grades, which were determined using undisclosed AI models trained on the class of 2020 and prior years students' data. Few things mattered more in life than where one went to college, and for many young people, their career, relationships, network, income, and, generally speaking, life was to be determined by what the UK's prime minister Boris Johnson labeled as the "mutant algorithm." Much like COVID-19 itself, this situation was repeated nearly identically in multiple countries, but the first instance of the crisis was with the International Baccalaureate Organization headquartered in Switzerland, which, on July 5, 2020, was the first to release its grades before individual countries released theirs. This public-sourced case examines the grading scandal, how it happened, and how it affected students worldwide.
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