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putting ai to work
putting ai to work
Sharma and Rani (2021) discuss how artificial intelligence (AI) and machine learning algorithms are critical as they can handle the enormous volume of data generated via technological devices, helping to analyze data for decision-making. Kelly (2020) discusses how AI can help users make sense of their data; for example, AI systems can help to analyze data and create insightful visualizations that users can easily interpret.
Watch this video for an example of how AI is being used in classrooms in China to analyze students' health and engagement levels to provide educational insights.
Wearables (headbands) measure students' level of concentration and this information is sent to parents and teachers (The Wall Street Journal, 2019).
This example may be jarring to many educators and parents, however, does this capture what the future will look like for learners in North America? If not this, how else do you envision 'Quantified Self' data be utilized for educational purposes?
(The Wall Street Journal, 2019)
ai assistant for quantified self
ai assistant for quantified self
There are opportunities to combine the capabilities of AI assistants with the quantified self movement. Imagine getting real-time alerts, reminders, or educational insights based on personalized data that is automatically collected via mobile devices and aimed towards improving learning or maximizing productivity.
data dashboards
data dashboards
Data-filled dashboards containing relevant data for educators about their students (similar to what was shown in The Wall Street Journal video above) may become the norm in all classrooms.
As illustrated in the two pictures below, imagine being able to use a mobile device to scan over students, with data instantly captured and summarized or a classroom where all students have holographic data charts above their heards, capturing and summarizing insights in real-time.
Educators have the opportunity to use this information to personalize learning and development programs or activities.
(The Economist, 2022)
Generated with Adobe Firefly. Prompt: Data dashboard in holograph above someone's head.
Poster of Gattaca directed by Niccol (1997), a dystopian movie based on eugenics.
Genetic data
Genetic data
Gattaca directed by Niccol (1997) has been such an iconic movie and may become more so as our health data continually becomes digitized as our world continues to digitize.
With movement towards DIY-at-home genetic testing kits of 23andMe, and other similar products, comes the advent of personalized medicine. The philosophical arguments presented by Beneduce and Bertolaso (2022) suggests hope for health care to move towards this 'Quantified Self' direction in terms of medicine.
Public aggregations of genetic data that has been used for academic purposes include the Harvard Personal Genome Project, the Open Humans Project. These projects allow individuals to voluntarily provide their own genetic or health related data to be aggregated and used for the collective good. Is this where our data will go to in the future? What are some ethical considerations or concerns when applying these policies to education?
Reflection Question:
How do you envision the future of AI and the quantified self? What changes or advancements do you envision?
How much do you trust the insights provided by AI and self-quantification tools? Why?
Share your response to this question on the ETEC 523 blog.
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