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Developing Institutional Level AI Policies and Practices: A Framework

WCET Frontiers

Many institutions have struggled to develop institutional-level policies. In a spring survey administered by WCET, only eight percent of respondents reported that their institution had developed and/or implemented at least one AI-related policy. The initial focus of campus policy discussions has centered on academic integrity.

Policy 59
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Is technology the ticket to bridging the £17bn gap in university income?

HEPI

To preserve the high quality of our sector and our ability to attract investment, talent and world-class research, it is vital that the higher education provider unit of resource be restored to 2012 levels as soon as practically possible. There are no two ways about it: technology is the answer to many of the ills the sector faces.

university leaders

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These finance leaders outline how investing in tech is helping drive down costs

University Business

This includes investing in technologies that can improve efficiency and internal visibility,” wrote the report’s authors Adam Cole and Andrea Espinola Wilson. Chief among them is updating their remote work policy and flexible work hours. Cybersecurity breaches can cost your institution millions of dollars on average.

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What can the UK learn from Australia’s University Accord?

HEPI

Great technology not only helps universities do more with less but is also a key strategy to retain staff, ensuring they are not dealing with menial tasks and instead focusing on meaningful work, be it responding to individual student needs, refining curricula, or improving research qualities. And this goes beyond the classroom.

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Rising higher ed leaders tackle campus challenges in EAB’s fellowship

EAB

Cooper Medical School of Rowan University Fostering sense of belonging among Black undergraduate students Melissa McGuire, Ph.D.,

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7 missteps university leaders must avoid in their AI approach

EAB

Embracing policies of academic integrity that penalized AI use will also ultimately embrace biases like unfairly targeting non-native English speakers, whose work might be easier to detect, when everyone is using AI. Instead, higher education leaders should proactively develop an institutional AI plan tailored to their unique needs and goals.