The Mindset for Creating Rude Coworkers
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Let's be Fwends is a journal about agility, organisations, technology, and the larger media landscape. And most importantly the role of all of us in all of that.
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Let's be Fwends #126:
The Mindset for Creating Rude Coworkers
Never attribute to malice that which is adequately explained by stupidity.
~ Robert J. Hanlon (attributed but disputed)
Welcome to this edition of Let's be Fwends. Today, we evaluate the consequences of two different mindsets for the quality of interaction in the workplace, poison LLMs, look bewildered at the idea of legalising all sorts of drugs in sports, look at some interesting facts about car batteries and their consequences to road furniture, and find out why insects are really attracted to artificial light.
The Mindset for Creating Rude Coworkers
Here's an interesting study on how mindsets influence human interactions in workplace settings.
In this study, the authors identified two different mindsets that directly impacted the way people treated their coworkers:
The first mindset was dubbed mechanistic, in which the focus is on the task and the efficient handling of it. For example, doctors who show a mechanistic mindset perform procedures on patients without letting them know what happens in order to save time.
The second mindset is a humanistic one, that centres on a persons self-worth and dignity. Medical personnel with a humanistic mindset can be observed comforting patients or complying with patients requests to ease discomfort or pain.
According to the study, adopting a mechanistic mindset is strongly associated with rude and uncivil behaviour, while personnel with a humanistic mindset showed civil behaviour and interactions throughout the study.
If you follow the idea that context defines mindset, these findings clearly show that you need to be careful how you think about your organisation: Thinking about our organisation in terms of factories, machines, and similar metaphors will promote a mechanistic mindset, that in turn create behaviour that is not helpful for teamwork.
How To Poison LLM Training Data in one Easy Step
The idea of adversarial machine learning is not new, but with the recent success of commercial Large Language Models that are trained non-consensually on openly accessible art, the concept rose to new importance. Nightshade is a tool that allows artists to "poison" their images in such a way that a model trained on them will respond to prompts in unexpected, but typically unwanted ways.
The creators say they developed the tool to help stop the practice of using artwork as training data without consent:
Used responsibly, Nightshade can help deter model trainers who disregard copyrights, opt-out lists, and do-not-scrape/robots.txt directives. It does not rely on the kindness of model trainers, but instead associates a small incremental price on each piece of data scraped and trained without authorisation. Nightshade's goal is not to break models, but to increase the cost of training on unlicensed data, such that licensing images from their creators becomes a viable alternative.
Let's Legalise "Enhancing" Athletes with Drugs. What Could Possibly Go Wrong?
I know that sports and performance enhancing techniques and medications are a blurry thing, and sometimes it's hard to tell why some things are illegal and some are not (or are illegal in one sport but totally fine in another).
But still (or maybe exactly for that reason), the "Enhanced Games" piqued my interest. I mean - something that claims that "Sports can be safer without drug testing" surely has quite a some entertainment value, right?
What is interesting about the self-touted "Olympic Games that does not have drug testing" is that it attracted some high-profile venture capitalists for its mission to normalise something that can only be described as excessive abuse of medication for performance enhancement with complete disregard of health concerns.
What I especially love is that they've created their own version of what "inclusive language" looks like - for example, calling taking illegal drugs in competition "Cheating" is harmful, and you're supposed to call that a "Demonstration of Science". (With referencing to no-one else than Lance Armstrong, who apparently is the victim of "weaponised language". Some things you simply can't make up.)
Some Interesting Trends in Batteries
Electric Cars Don't Work Well on Modern Traffic Infrastructure
Talking about batteries - they're the reason why electric vehicles are between 20% and 50% heavier than gasoline-driven vehicles. Because of this (and the lower center of gravity, because of the placement of the batteries), barriers are not strong enough to hold cars on the road in case of an accident. Now, engineers are scrambling to figure out how to build guardrails that are strong enough to withstand the impact of electric vehicles, and furthermore, how to replace the outdated ones.
A perfect example of what happens when you introduce a change in a complex adaptive system - as one agent evolves (cars getting heavier), the rest of the system reacts to that change.
Why Flying Insects Gather at Artificial Light
It's not because they steer directly towards the light. Instead, they express the same behaviour as during daytime: They tilt their backside towards the light (to stabilise their flight paths), which creates the seemingly erratic flight paths towards artificial light sources at night.
Gives the phrase flying by the seat of your pants a whole new meaning ...
That's it for this edition of Let's be Fwends. Maybe lifting your head into the approximate location of the sun not only helps your circadian clock, but also keeps you out of trouble. Don't trust your 🍑 with navigation.
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