#human work

[tebaude]

i realised that part of my shame journey is going to have to involve saying real things about myself?? to other people???? real actual listening humans i am trying to have some sort of emotional connection with on some level that's not just deflecting?

[harrypotterhousequotes]

RAVENCLAW: "The most familiar facts are often hardest to understand." –Charlotte Perkins Gilman (Human Work)

[books0977]

Human Work. Charlotte Perkins Stetson Gilman. New York: McClure, Phillips & Co., 1904. First edition, first binding.

Represents the first groundbreaking analysis on the equal importance of work in the lives of men and women. Noted feminist Gilman maintains the notion that it was "sexuo-economic oppression of women" and not women's biology that kept women from achieving in all areas of work. Accusing men of appropriating certain work as "men's work" and masking the process as a biological locus rather than an exercise in power relations, Gilman asserts that men created an economic dependence that has prevented women from success in the workplace.

[pinksiamese]

THIS

It's this

[poetrystudiopractice]

a reflection

i cannot add all the photos at once here, so i’m sharing a link to the second notebook created with the impulse of this class... stay safe, love, maria~

[tebaude]

I got out the notebook to write down some things I wanted, some goals and some things to build on. instead, yeah, it's still a wall. it bites back.

I find some of it when I look back at school: I wanted to do well and I stopped being able to. you have a ready-made frame for success - so much easier than having to make your own! - and just, for people who've always succeeded at this, I don't know how to describe it, what the irrelevance of your wanting becomes.

shame - I'm naming it in case that will help at all. I guess this happens out of a confluence of so many factors: you're bright so you are construed to not need help, "you can do anything you put your mind to" - seriously a phrase I've been told over & over & over but they don't know they've conditioned you to never be able to ask for help so that you actually CAN do things? it's a whole bad, bad wall of shame built out of all of that - out of failing other people's expectations, or at least what they told you they are. it's a mess.

I just watched the Queer Eye with Tyreek so the way he thought he'd failed to live up to his mum's wishes for him when he hadn't is on my mind. but also a couple of things today about asking for help. it might be that that's part of a way out. I do know that when I talk to people I get aspirations, ghost wants, at least starting, little dreams. I then have to be with the shame next. I don't know, I really don't know, because it's so strong that when I get close to it my brain fogs so intensely in self-protection, and the idea of coming close to it as part of a process gives me that foggy terror. but that's how I don't move on.

[guestu]

How AI will change the way we make decisions

With the recent explosion in AI, there’s a natural concern about its potential impact on human work and the loss of jobs. Which industries will be most affected, and which skills will be most in demand?

Harvard Business Review provides the answers to these questions and suggests an alternative approach. According to economic theory, people who display good judgment will become more valuable. Here are some tips of Harvard Business Review:

 Why AI does and why it’s useful

Recent advances in AI are best thought of as a drop in the cost of prediction. Prediction is about using data that you have to generate data that you don’t have. We do that translating large amounts of data into small, manageable amounts. A classic prediction problem is using images divided into parts to detect whether or not the image contains a human face.

Prediction is useful because it helps improve decisions. Other important input is judgment. A good example is a credit card network deciding whether or not to approve each attempted transaction. The idea is to allow legitimate transactions and decline fraud and thy use AI to predict whether each attempted transaction is fraudulent.

However, even the best AIs aren’t 100 % reliable and the people who have run the credit card networks know from experience that there is a concession between detecting every case of fraud and inconveniencing the user. This means that to decide whether to approve a transaction, the credit card network has to know the cost of mistakes. It would be worse to decline a legitimate transaction or to allow a fraudulent transaction? No AI can make that judge, just humans. This decision is what we call judgment.

 What judgment entails

Judgment is the process of determining what the reward to a particular action is in a particular environment. It is how we work out the benefits and costs of different decisions in different situations.

Credit card fraud is an easy decision to explain in this regard. Judgment involves determining how much money is lost in a fraudulent transaction, how furious a legitimate customer will be when a transaction is declined, as well as the reward for doing the right thing and allowing good transactions and declining bad ones. Humans learn by experience, observing their mistakes.

They will specialize in judging the costs and benefits of different decisions, and then that judgment will be combined with machine-generated predictions to make decisions.

 Setting the right rewards

It is true that AIs can also learn from experience and a good technique is reinforcement learning whereby a computer is trained to take actions that maximize a certain reward function. For instance, DeepMind’s AlphaGo was trained this way to maximize its chances of winning the game of Go. Games are often easy to apply this method of learning because the reward can be easily described and programmed – shutting out a human from the loop.

In fact, even if an organization is enabling AI to make certain decisions, getting the payoffs right for the organization as a whole requires an understanding of how the machines make those decisions. There are some types of prediction mistakes more likely and a machine can learn the wrong message.

 Overall, it’s too soon to know if machine prediction will decrease or increase the amount of work available for humans in decision-making. It is true that machine prediction will substitute human prediction in decision-making, but machine prediction is a complement to human judgment. Cheaper prediction will generate more demand for decision-making, so there will be more opportunities to exercise human judgment.