Around 1200 BC, the Shang Dynasty of China already had factory systems that produced thousands of bronzes for daily and sacrificial purposes. In this early example of mass production, the bronze casting process required intricate planning and coordination among a large number of workers who completed their individual tasks in a precise sequence.
A thousand years later, similar complicated craftsmanship were also used to manufacture the famous Terracotta Warriors and Horses. These statues were "manufactured by an assembly line production system that laid the foundation for large-scale production and commerce."
Some scholars speculate that these early forms of prescriptive work (prescripTIve-work) technology have played a very important role in the formation of Chinese society. Together with other factors, they make people accept the social philosophy of bureaucracy that emphasizes hierarchy, and make people believe that there is a simple and correct way of everything.
When industrialized factories were born in Europe in the nineteenth century, even capitalist critics such as Engel admitted that regardless of whether the economic system was capitalism or socialism, mass production was a necessary condition for centralization. In the twentieth century, theorists such as Langdon Winner extended this idea to technology. He believes that (for example) the atomic bomb should be regarded as an "inherent political product" because its "lethal property requires that it should be controlled by a centralized rigid command hierarchy."
Today, we can extend this idea even further. Consider machine learning algorithms-this is the most important general-purpose technology used today.
A key feature of machine learning algorithms is that their performance will improve as the data increases. Therefore, the use of these algorithms has created a technical impetus to process information about people into recordable and callable data. Like large production systems, they are "inherently political" because their core functions require certain social behaviors and hinder other social behaviors. In particular, the dissemination of machine learning is directly opposed to the individual ’s desire for privacy.
A system based on the public availability of information about individual members of society seems to fit the socialists (communitarians) such as sociologist Amitai Etzioni, who believe that the restriction of privacy enforces social norms means. But unlike socialists, algorithms do not care about social norms. They only focus on making better predictions, and this can be achieved by turning more and more areas of human life into data sets that can be mined.
Algorithm evaluation is not new. Scholars such as Oscar H. Gandy warned that we are transforming into a society of record and ranking, and demand more accountability to correct errors caused by technology. But unlike modern machine learning algorithms, old evaluation tools can be understood quite thoroughly. They make decisions based on relevant normative and empirical factors. For example, carrying many credit card debts is detrimental to a person ’s credibility. This is no longer a secret.
On the contrary, the new machine learning technology digs into large data sets and can find the correlation between things that are predictable but not fully understood. In the workplace, algorithms can track employee conversations, where they have lunch, and how much time they spend on computers, phones, or meetings. With this data, algorithms can develop complex productivity models that far exceed our common sense intuition. In an algorithmic elite system, what the model requires, what becomes an excellent standard.
Nevertheless, technology is not fatal. We decide technology before technology decides us. Business leaders and decision makers can develop and deploy technology according to their institutional needs. We have the ability to arrange a privacy network around sensitive areas of human life to protect people from harmful data uses, and require algorithms to balance the accuracy of predictions with values ​​such as fairness, accountability and transparency.
But before we follow the logical flow of natural algorithms, more elitism is inevitable. This change will profoundly affect our democratic system and political structure. If the current business and consumer culture continues, we will soon have more similarities with virtuous politics and socialist traditions, rather than our own individualism and liberal democratic traditions. If we want to change trends, we must put our own political responsibility ahead of technology.
Which is the most welcome kid laptop for entertainment and online learning? 10.1 inch laptop is the best choice. You can see netbook 10.1 inch with android os, 10.1 inch windows laptop, mini laptop 10.1 inch 2 in 1 windows, 10.1 inch 2 In 1 Laptop with android os. Of course, there are various matches of memory and storage, 2 32GB or 4 64GB. Our suggestion is that 10.1 inch android 32GB laptop, 10.1inch 32GB or 64GB Solid State Drive windows laptop. Except 10.1 inch Student Laptop , there are 11 Inch Laptop, 15.6 Inch Laptop, 14 Inch Laptop , also option here.
Besides, other advantages you can see on 10.1inch Budget Laptop For Students, for example, lightweight, competitive cost, portability, Android or Windows OS, rich slots, energy saving cpu, etc.
As a professional manufacturer, can provide free custom service, like mark client`s logo on laptop cover, opening system, inner color box, manual, boot. Produce as your special requirement on parameters, preinstall apps needed, etc. What you need to do is very simple, confirming PI, including price, delivery time, parameters, etc.
10.1 Inch Laptop,Netbook 10.1 Inch,10.1 Inch 2 In 1 Laptop,10.1 Inch Windows Laptop,Mini Laptop 10.1 Inch
Henan Shuyi Electronics Co., Ltd. , https://www.shuyielectronics.com