The four types of managers based on their loyalty and giving/taking credit characteristics. Model by Bas Wallet.
Category: objects-in-mirror
Critical reflections
Pollution of the symbolic (virtual) environment
“The fusion of trade, politics, and communication has brought about the sophisticated one-dimensional character of our symbolic environment, which is as least as menacing as the pollution of the natural environment (van Toorn as cited in Dinot 2009:180)”
“So, why do we keep on engaging? Biochemistry is a complicated milieu, but the relationship between the neurotransmitter dopamine and technologically motivated behavior is well understood. According to Psychology Today, dopamine “helps control the brain’s reward and pleasure centers […] emotional responses, enabling us not only to see rewards but to take action to move toward them.” Dopamine, as Susan Weinchenk notes, “makes us curious about ideas and fuels our searching for information.” We get a spike in dopamine after performing information-seeking behavior like checking social media accounts for new activity. Repeated dopamine-seeking behavior highlights the downside of seemingly innocent actions like notification consumption. We might search for one data point, only to fall down a well of multiple searches that cause a mild dissociative hyper-focus where we lose sense of how much time we’ve spent.”
Quoted in The snake that eats its tail, written by Rachel M. Murray
OpenAI: Gizmo tool
OpenAI will announce the Gizmo tool, which specializes in creating, managing, and selecting custom chatbots.
Gizmo is expected to bring the following features:
– Sandbox – Provides an environment to import, test and modify existing chatbots
– Custom actions – Define additional functions for your chatbot using OpenAPI specifications
– Knowledge files – Add additional files that your chatbot can reference
– Tools – Provides basic tools for web browsing, image creation, etc.
– Analytics – View and analyze chatbot usage data
– Drafts – Save and share drafts for chatbots you create
– Publish – Publish your finished chatbot
– Share – Set up and manage chatbot sharing
– Marketplace – browse and share chatbots created by other users
There will also be a Magic Creator or Magic Maker to help you create chatbots:
– Define your chatbot with an interactive interface
– Recognize user intent and create chatbots
– Test the created chatbot live
– Modify chatbot behavior through iterative conversations
– Share and deploy chatbots”
AI won’t solve your problem, but it can help
AI won’t solve your problem, but it can help. But it can only do that if you put in the neccessary-but-unsexy work on content, process, people and governance first. Otherwise you risk wasting your money, or even making things worse.
Sharon O’Dea on LinkedIn
Do We Collaborate With What We Design?
(..)
Humans cannot collaborate with machines. This is the answer to the question that this paper set out to tackle. By scrutinizing the concept of collaboration, we find not that current machine action simply lacks the necessary conditions for collaboration, but rather that there is no coherent framing for which collaboration could be a meaningful term with regards to designed systems. Strictly speaking, collaboration requires the interactions of peers, none of whom could be substituted, all of whom are pursuing goals, all of whom bring unique concepts and skills to a shared project. But even many aspects of joint action that humans might participate in below the “collaborator” level of cooperation are not available to AI systems. The autonomy to join or withdraw from a collaboration, or (co)determine ends, is not available in a designed system, nor is a principal agency, not because this is disallowed but rather because the system’s status as a designed product of an organization makes this incoherent. For these same reasons, the words “teammate,” “partner,” and others are also inappropriate to use when describing a human and a machine acting together on a task.
(..)
Katie D. Evans, Scott A. Robbins, Joanna J. Bryson: Do We Collaborate With What We Design?
Why human creativity beats generative AI
Inspired by a talk by Ovetta Patrice Sampson, Config 23
We are visionary.
We think laterally.
We are neurodivergent.
We come up with ideas without being asked to.
We take risks.
We consider context.
We accept uncertainty.
(tbc)
Clocks and Clouds
Karl Popper, the great philosopher of science, once divided the world into two categories: clocks and clouds. Clocks are neat, orderly systems that can be solved through reduction; clouds are an epistemic mess, “highly irregular, disorderly, and more or less unpredictable.” The mistake of modern science is to pretend that everything is a clock, which is why we get seduced again and again by the false promises of brain scanners and gene sequencers. We want to believe we will understand nature if we find the exact right tool to cut its joints. But that approach is doomed to failure. We live in a universe not of clocks but of clouds.
Jonah Lehrer published in The Atlantic
Over-reliance on lean methods
Our products don’t exist in a vacuum, nor should our processes. From my perspective, there is an over-reliance on methods such as Agile, Lean UX and design sprints that rush product teams towards short term solutions when building technology. These rapid processes make it easy to forget that
problems shift based on our perspective and complexity increases at different scales.
Linear processes often simplify the types of questions asked and time spent unpacking the problem, making it difficult to design a product that can handle complexity at scale.
From the perspective of the song …
From the perspective of the song, the song hired the human to promote itself.
Unknwon
Progressive enhancement of user experience
- Purposeful
- Functional
- Accessible
- Usable
- Delightful
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