May your bones be broken as often as the Ten Commandments
attention?
States bankrupted and begging
like the out of work and discarded,
the old and ill tossed
to the angry streets
the moneyed smug feeding
like flies crazed on carrion
from Tell MEdia Dragon of Golden Lane Fame
New and interesting Jordan Peterson article: “He speaks in rapid-fire, um-less sentences. He doesn’t smile much.” Like Dr Cope, Peterson is one of the most influential public intellectuals today.
Fake celebrity stories are still hijacking Facebook search results
What We Misunderstand About Willpower
"It turns out that self-control, and all the benefits from it, may not be related to inhibiting impulses at all. And once we cast aside the idea of willpower, we can better understand what actually works to accomplish goals, and hit those New Year's resolutions." … Read More
Bernie Sanders (@SenSanders)
If you think the shutdown we're experiencing right now isn't related to our disastrous campaign finance system, you would be dead wrong. pic.twitter.com/oDdwS0LQi8
Paper – The accuracy, fairness, and limits of predicting recidivism
The accuracy, fairness, and limits of predicting recidivism, Julia Dressel and Hany Farid. Science Advances 17 Jan 2018: Vol. 4, no. 1, eaao5580. DOI: 10.1126/sciadv.aao5580
“Algorithms for predicting recidivism are commonly used to assess a
criminal defendant’s likelihood of committing a crime. These predictions
are used in pretrial, parole, and sentencing decisions. Proponents of
these systems argue that big data and advanced machine learning make
these analyses more accurate and less biased than humans. We show,
however, that the widely used commercial risk assessment software COMPAS
is no more accurate or fair than predictions made by people with little
or no criminal justice expertise. We further show that a simple linear
predictor provided with only two features is nearly equivalent to COMPAS
with its 137 features.”
A TV character’s personality is based on:
· Motivation:
They need / want / are hungry for something and spend their story trying to get that something. We come to understand exactly what motivates them to be driven that way and understand that compulsion.
They need / want / are hungry for something and spend their story trying to get that something. We come to understand exactly what motivates them to be driven that way and understand that compulsion.
· Vulnerability:
They are human, worried, fearful of something. And we feel for them.
· Conflict:
They must make hard choices. We know what that’s like.
· Connectivity:
To us, to me, to the other characters. Life is not an island.
· Complexity:
Layered, good, bad, and/and, multi-dimensional and multi-layered.
· Strength:
Big characters / leaders are impressively good at something – anything – that matters and sets them apart.
· Weakness:
And they must be flawed. Just like all of us.
· Emotion:
They must feel and be seen to feel.
In fact, the more I thought about this, the more I thought a great TV character is developed the same way we develop a Brand to become a Lovemark. By adding Mystery, Sensuality and Intimacy to Respect and Trust.
A compelling character has a memorable name, a history with some mystery in it, some secrets, a look, a voice, a touch, and makes us want to know them, to feel for them and to join them.
To compete at the speed of digital, you need to unleash your strategy, your structure, and your people: “…In this article, we’ll share these emerging elements of the organization of the future. While there is no set formula for success, we’ve seen versions of these elements at so many companies that we think they provide at least the organizational outline to win (Exhibit 1). Along the way, we’ll try to dispel some common misconceptions (too risky! too inefficient! too time consuming to set up!) of what such an organization really means. We know you don’t want your company to undergo yet another reorg—and another one a few years after that. Consider this a road map out…”
Baywatch hero drone saves silly struggling swimmers Down Under from going down under
