Eps 47: Algorithmic gaze
— The too lazy to register an account podcast
In addition to the offline production cycle, the algorithm is an additional rhythmic system that forces us into this fashion system.
As part of commercial rhythms, algorithms mystify the influential effect new media has on our consuming habits, affecting our ability to consciously position ourselves within the fashion system.
Overall, fashion uses the attendance of natural rhythms in daily life and conditions these in order to affect its consumer.
| Seed data: | Link 1, Link 2 |
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| Host image: | StyleGAN neural net |
| Content creation: | GPT-3.5, |
Host
Isobel Graves
Podcast Content
Jentery and Sayers suggest that computer vision algorithms represent a new kind of power called algocracy, or the domination of algorithms. They argue that we are so deeply embedded in our modern infrastructure that algorithms have begun to shape our behavior. Recognizing where there is a connection between the Instagram algorithm and the team that creates and monitors it can be applied to other platforms with similar algorithms, and vice versa.
Computer vision is generally associated with a wide range of applications in health, education, transportation, and other sectors. Examples include medical imaging, medical diagnostics, computer vision, social media, health monitoring, safety, data analysis, and even medical research.
Machine learning essentially trains a machine (like a computer or software) to act like a human, and with this training comes man - like a bias. For facial recognition software, a training record would be a series of photos, such as a photo of a face, that the algorithm can use to learn what is and is not in the face. The algorithm is used because by learning from the training kit, it will be able to recognize which faces are in a new photo and which are not.
Imagine an industry in which we train and test algorithms that seem to be a natural parallel to humans: images that look like lines or blobs, lacking an obvious, immediate structure. The algorithm, trained to see the world on our behalf, jumps from one image to the next until it learns what is in the image and what is not.
For example, there are abstract smears designed to label Google's algorithm as inappropriate content. Print is an optical illusion; only computers can see hidden images, and they are programmed to produce something new. Algorithmic View does some very useful things, but only if it is programmed for the right purposes.
Machine vision could make the world safer by steering cars safely off the road, and it could save lives by speeding up medical diagnoses, according to a recent study in The New York Times.
But if we really want to use this technology forever, we need to better understand it and consider its potential applications, such as self-driving cars. For this research project, I wanted to explore creative applications of AI by gaining insights into the artificial thought process of computers.
How do these views influence our own view of reality, and how can we better understand the images computers have of us by decoding them? In this week's WIRED, I delve into the impact algorithms have on the human world. I explore what happens when we let algorithms make our lives and decisions, and find out how machine learning alters thought literature, revealing how the algorithmic gaze of tech giants perpetuates ugly prejudices in the offline world and beyond.
You will find that, in a world increasingly dominated by code, you are making a little room for mankind. You will see how London's streets defy self-driving cars and encounter ants that teach us that even the most complex code only reflects what we already see in the natural world.
Jentery and Sayers argue that very little work has been done on critical technical practices that interweave aesthetics with the body. Researchers working in the field of computer vision work in a limited space where their work is not defined by public policy. I want to explore the disciplinary power that algorithmic authorities wield when they see through the vision of computers, and the role of aesthetics in it.
Last week I wrote about a scenario in which the subject of the viewer's gaze internalizes his own subjectivation.
The Algorithmic Justice League aims to take different perspectives into account by engaging those who are often excluded from this conversation, adding them and showing how we can use one of the most widely used technologies in our society. From the outset, our mission has been to combat algorithmic bias, which is coded looks and can lead to social exclusion and discriminatory practices. We believe that this has the potential to shape our understanding of technology that is limited to one group of people.
Technology permeates so many aspects of our lives, and if it is not applied and adapted to the public interest and social justice, there will be serious mistakes and missed opportunities.