How Could AI Help Make Evaluations More Inclusive

How Could AI Help Make Evaluations More Inclusive?

In the modern educational landscape, exams should be a tool for everyone, ensuring a learner’s aptitude is genuinely reflected. Yet, biases have historically distorted their fairness. Enter AI—a tool with potential to revolutionize inclusive assessment, though not without hurdles. A Real-world Dilemma: Bias in Tests and Exams Exams have traditionally catered to the majority, often overlooking minority groups. From language barriers to socio-economic disparities, biases make assessments less of an accurate measure of knowledge and more of a reflection of privilege. The Global Push for Fairer Assessments The movement towards inclusivity is not just a regional issue. From the UK to the US, institutions recognize the need for change. Practices such as “test-optional” admissions and accessible guidance like Ofqual’s are strides in the right direction. AI’s Role in Reshaping Assessments The rise of AI in learning and assessment cannot be ignored. From AI-created questions to the potential risks of cheating using tools like ChatGPT, the realm of AI-assisted education is vast and still developing. Can AI Foster or Hamper Inclusivity? The bias in AI is a genuine concern. Tools like ChatGPT may inadvertently reflect societal biases, potentially leading to further marginalization in assessments. However, these tools are in their infancy, and their potential for positive change is vast. The Potential of AI for Equitable Assessments As AI matures, there’s hope it will help make exams more unbiased. By identifying potential bias in questions, offering personalized learning, and even aiding in the fight against cheating, AI may well become the great equalizer in education. A Glimpse into the Future of AI and Assessments While challenges persist, AI’s promise lies in its continuous evolution. With the right training and approach, AI has the potential to make assessments more considerate, respectful, and truly reflective of a student’s abilities.

Read more
Microsoft and Epic Partner to Leverage Generative AI in Electronic Health Records

Microsoft and Epic Partner to Leverage Generative AI in Electronic Health Records

Microsoft and Epic, two major players in the healthcare industry, are joining forces to improve the accuracy and efficiency of electronic health records (EHRs) through the power of generative artificial intelligence (AI). EHRs are essential tools for healthcare providers, but they can be time-consuming, prone to errors, and even burdensome at times. By using AI algorithms to automatically fill in missing information, EHRs can become more complete, accurate, and easier to use, freeing up clinicians to focus on patient care. What is Generative AI and How Can It Improve EHRs? Generative AI uses machine learning to generate new content, such as text, images, and even entire websites. In the context of EHRs, generative AI can be used to automatically fill in missing information, suggest diagnoses, and even predict future health outcomes based on historical data. Microsoft and Epic’s partnership aims to accelerate the adoption of generative AI in healthcare and improve patient outcomes. The partnership will integrate the Microsoft Azure OpenAI Service with Epic’s EHR platform, extending natural language queries and interactive data analysis to Epic’s self-service reporting tool, SlicerDicer. UC San Diego Health, UW Health in Madison, Wisconsin, and Stanford Health Care are among the health systems already deploying the integrated systems, leveraging Epic’s new capabilities to automatically draft message responses. Benefits and Risks of Generative AI in Healthcare The potential benefits of generative AI for healthcare are significant. By automating tedious and error-prone tasks, clinicians can spend more time with patients, and EHRs can become a valuable source of insights that can help improve care quality and reduce costs. However, there are also potential risks associated with the use of generative AI in healthcare, such as bias if the algorithms are trained on incomplete or biased datasets. How Microsoft and Epic are Developing Ethical AI Solutions for Healthcare To mitigate these risks, Microsoft and Epic are committed to developing transparent and ethical AI solutions that are rigorously tested and validated. Eric Boyd, corporate vice president, AI platform, for Microsoft, argued that the challenges facing healthcare systems and their providers demand an integrated approach. “Our expanded partnership builds on a long history of collaboration between Microsoft, Nuance, and Epic, including our work to help healthcare organizations migrate their Epic environments to Azure,” he said in a statement. Healthcare Providers Adopting Generative AI to Improve EHRs By leveraging the power of generative AI, healthcare providers aim to improve the accuracy and efficiency of EHRs, ultimately leading to better patient outcomes. Generative AI is increasingly viewed as a potential co-pilot for multiple players in the healthcare space and is a key topic at this year’s HIMSS conference, where potential use cases applied to business and clinical challenges – like clinician burnout and achieving interoperability – are being explored. “Our exploration of OpenAI’s GPT-4 has shown the potential to increase the power and accessibility of self-service reporting through SlicerDicer, making it easier for healthcare organizations to identify operational improvements, including ways to reduce costs and to find answers to questions locally and in a broader context,” said Seth Hain, senior vice president of research and development at Epic, in a statement. In conclusion, Microsoft and Epic’s partnership to harness the power of generative AI to improve EHRs is an important step towards improving patient outcomes. By automating tedious and error-prone tasks, clinicians can spend more time with patients, and EHRs can become a valuable source of insights that can help improve care quality and reduce costs. With the potential benefits of generative AI for healthcare, it is crucial to develop transparent and ethical AI solutions that are rigorously tested and validated to mitigate the potential risks.

Read more