Category Archives: research

Google and Microsoft’s chatbots are already citing one another in a misinformation shitshow

Microsoft’s Bing said Google’s Bard had been shut down after it misread a story citing a tweet sourced from a joke. It’s not a good sign for the future of online misinformation.

Marshall McLuhan and the future of digital research

Robots Won’t Save Japan addresses the Japanese government’s efforts to develop care robots in response to the challenges of an aging population, rising demand for eldercare, and a critical shortage of care workers. Drawing on ethnographic research at key sites of Japanese robot development and implementation, James Wright reveals how such devices are likely to transform the practices, organization, meanings, and ethics of caregiving if implemented at scale.

This new form of techno-welfare state that Japan is prototyping involves a reconfiguration of care that deskills and devalues care work and reduces opportunities for human social interaction and relationship building. Moreover, contrary to expectations that care robots will save labor and reduce health care expenditures, robots cost more money and require additional human labor to tend to the machines. As Wright shows, robots alone will not rescue Japan from its care crisis. The attempts to implement robot care instead point to the importance of looking beyond such techno-fixes to consider how to support rather than undermine the human times, spaces, and relationships necessary for sustainably cultivating good care.

Language And The Future

It has been an interesting week of consulting conversations and workshops around the application of language and culture in the innovation process. Mainly the center of the conversation around how semiotics reveals our participation in the linguistic systems that shape our world.

As more companies become excited by the possibilities of new generative AI tools, we must consider how such tools are rooted in existing easily accessible corpuses. No fault of their own. They need to start somewhere. An explicit language corpus is available.

However, the real ability to suss out implicit signifiers and analyze the relationships between explicit and implicit signifiers is the role of humans. Humans can better leverage generative AI tools as augmentation of classification and the patterning of evolving meaning in culture.

Innovation and design foresight must be mandated to make the relationship between the explicit and implicit, the knowns and unknowns, in the world clearer.

It all starts to get really interesting when we begin to better understand how to use these tools to move us beyond our baked-in and residual idea of how the world should work. And our laziness in letting the machine do the easy work for us and ending there.

Design affordances open up when we understand the ways language holds us back or tricks us into repeating remixes of old ideas. The future of work is embedded in the design affordances that constitute its meaning. The existing tension between corporate quitting and corporate surveillance begs for a better articulation of how language is working to undermine the system we hope to sustain.


Here’s why ChatGPT raises issues of trust

ChatGPT doesn’t produce sentences in the same way a reporter does. ChatGPT, and other machine-learning, large language models, may seem sophisticated, but they’re basically just complex autocomplete machines. Only instead of suggesting the next word in an email, they produce the most statistically likely words in much longer packages.

Because ChatGPT’s truth is only a statistical truth, output produced by this program cannot ever be trusted in the same way that we can trust a reporter or an academic’s output. It cannot be verified because it has been constructed to create output in a different way than what we usually think of as being “scientific.”

How do we stop the robot takeover? As AI gets smarter, meet the academics on a mission to save humanity from the matrix

The dawning of AI’s golden age poses all manner of tricky questions. If we allow machine intelligence to do our jobs and clean our houses, pick our music and television, generate our art and essays, judge our legal cases and diagnose our illnesses, what will be left for us to do? What’s so special about being human in the age of advanced artificial intelligence? What’s so special about being human at all?

Alarmed by A.I. Chatbots, Universities Start Revamping How They Teach

Across the country, university professors like Mr. Aumann, department chairs and administrators are starting to overhaul classrooms in response to ChatGPT, prompting a potentially huge shift in teaching and learning. Some professors are redesigning their courses entirely, making changes that include more oral exams, group work and handwritten assessments in lieu of typed ones.

𝘿𝙖𝙩𝙖 𝙅𝙪𝙨𝙩𝙞𝙘𝙚 𝙖𝙣𝙙 𝘼𝙡𝙜𝙤𝙧𝙞𝙩𝙝𝙢𝙞𝙘 𝘼𝙘𝙘𝙤𝙪𝙣𝙩𝙖𝙗𝙞𝙡𝙞𝙩𝙮 Syllabus and Reading Lis

Margaret Mead Imagined Different Futures

For those anxious about the state of the world, Mead’s celebrated work shows how anthropology can help guide alternative futures.

If Samoan adolescents had a (comparatively) easier time adjusting to their maturing sexuality, as Mead claimed, couldn’t people in the U.S. raise their children in a similar way? Mead quickly dismissed that idea, but then offered up another possibility: Familiar U.S. ideals of freedom and liberal tolerance needed to be extended to adolescent women as they explored their own sexuality.