User:Haileywriter/sandbox

My article: Artificial intelligence in heavy industry

Below is only a rough draft. The finished product is in the link above.

Potential Negatives

In September 2015, the German car company Volkswagen had an international scandal. The software in the cars recognized when cars were being tested for emission levels and activated emission controls of nitrogen oxide gases (NOx gases). Once on the road, the emission controls deactivated and the NOx emissions increased up to 40 times. NOx gases are harmful because they contribute to several significant health problems, including respiratory problems asthma. Further studies have shown that additional emissions could cause over 1,200 premature deaths in Europe and result in $2.4 million USD in lost productivity. The problem comes with machines unintentionally harming the environment. It's important for the AI algorithms to be managed and studied.

AI trained to be environmentally conscious may have mistakes in the algorithms which can lead to AI performing potentially negative effects on the environment. Algorithms trained on biased data will produce biased results. The COMPAS judicial judicial decision support system is one example of biased data producing unfair outcomes. When machines develop learning capacity and the ability to make decisions not written into the code by a programmer, the mistakes can be hard to trade and also hard to see. That's why management and examination of AI performance is essential.

Potential Benefits

Self-driving cars have the potential to be beneficial to the environment. They can be programmed to the the most efficient route and reduce idling which could result in reduced fossil fuel consumption and greenhouse gas (GHG) emissions. The same could be said for the heavy machinery used int he heavy industry. AI have the ability to see the path clearly, whereas humans are prone to the occasional error.

Artificial Intelligence in the Heavy Industry

Artificial intelligence can find patterns, trends, associations, discoIn this case, the software was caught and the responsible parties were held accountable. This scandal bellied the concern of the public that AI systems can start accidentally producing negative consequences while trying to be environmentally good for the environment.ver inefficiencies, learn and become more efficient, execute plans, predict future outcomes based on historical trends, and inform fact-based decisions. They can perform thousands of permutations faster than humans and perform dangerous jobs without the risk of human loss.

Artificial intelligence uses machine learning, a type of AI that allows computer programs to adjust when they become exposed to new data, which allows them to "learn" without it being explicitly programmed. Altogether, AI in the heavy industry can optimize asset management, improve operational performance, identify efficiencies, and decrease downtime. Though it can also decrease employment due to jobs being taken over by AI.

History

The trend towards increased automation can be traced back to the Great Recession, which forced many businesses to operate with fewer workers and cost many workers their jobs. The term, artificial intelligence, was first defined in 1956. Alan Turning, a young British polymath, explored the mathematical possibility of artificial intelligence. Turning suggested, in his 1950 paper, Computing Machinery and Intelligence, that since humans can use available information as well as reason to solve problems and make decisions, it was only logical that computers could as well. He also discussed how to build intelligent machines and how to test their intelligence.

Designed by Allen Newell, Cliff Shaw, and Herbert Simon, the Logic Theorist, was a program designed to mimic problem solving skills of a human and was funded by Research and Development Corporation. It's considered by many to be the first artificial intelligence program and was presented at the Dartmouth Summer Research Project on Artificial Intelligence by John McCarthy and Marvin Minsky in 1956.

Potential Benefits

AI-driven machines promise an easier manufacturing process and many benefits with each new advancement. Technology is creating new ways to automate tasks, and increasing the intelligence of human and machine interaction. Some benefits to AI are directed automation, 24x7 production, a safer operational environment, and condensed operating costs.

Directed Automation

AI and robots are capable of doing recurring activities on repeat without error, designing the production model with rising competence, building their own automation solutions, eradicating human errors and delivering superior levels of quality assurance.

24x7 Production

While humans work in shifts to ensure production is continuous and without error, robots are capable to work all hours in the production line. They are not limited by human physical limitations. Businesses can expand their production capabilities and meet the high demand of their global customers since production would be increased due to the around-the-clock work performance.

Safer Operational Environment

More AI means less human labor doing dangerous and often strenuous work. Logically speaking, with less humans and more robots performing risky activities, the number of workplace accidents will decrease. It also gives more opportunity for exploration because companies aren't risking human life but robotic life.

Condensed Operating Costs

With AI taking over day-to-day activities, business will have a considerably lower operating cost. Instead of employing humans to work shifts, they can simply invest in AI. The cost would would come from maintenance afterward its purchase and creation.

Additional Benefits of AI

AI and industrial automation has advanced considerably in these past few years. There have been many new techniques and innovations, such as the advances in sensors and the growth of computing power. AI helps machines gather and extract data, acknowledge patterns, adapt to new things through machine intelligence, learning, and speech recognition.

With AI, manufactures will be able to create quick data determined decisions, advance process effectiveness, minimize operational costs, facilitate product development, and facilitate superior scalability.

Potential Negatives

High Cost

Though the price has been decreasing in the past few years, individual developments can still be as high as $300,00 for a basic AI. Small businesses with a low initial capital may have difficulty finding the funds necessary to take advantage of the benefits that AI can bring. For larger companies, the price of AI may be higher, depending on how much AI is involved in the process. The high price tag makes utilizing AI hard for many companies.

Reduced Employment Opportunities

Jobs will be gained by AI; however, some jobs may be lost because AI has replaced them. Any job that features repetitive tasks are at risk of being replaced. In 2017, Gartner predicted 500,000 jobs would be created because of AI, but also predicted that up to 900,000 jobs could be lost because of this. These figures are for jobs only within the United States. In 2014, Google, valued at $370 billion, had only 55,000 employees which is just a tenth of the size of AT&T's workforce in the 1960's. This is one affect of AI in the work place. As AI machines perform jobs that humans can, they can be more cost effective than humans themselves.

AI Decision Making

AI is only as intelligent as the individuals responsible for its initial programming. In 2014, an active shooter situation led to people calling Uber to escape the area. Instead of recognizing the dangerous situation, the algorithm Uber used saw a spike in demand and increased its prices. This type of situation can be dangerous in the heavy industry, where a faulty decision choice could cost lives or injuries.

Affect of AI in the Manufacturing Industry

The number of industrial robots has increased greatly since the 2000's. The prices of robots, which are capable of operating all hours of the day without interruption, make them cost-competitive with human workers. In the price sector, computer algorithms can execute stock traders much faster than a human. It's done in a fraction of a second. With these technologies becoming more accessible and cheaper to the world, in the future, they will be implemented more and humans might becoming increasing replaced with AI.

Experts disagree how much automation technologies will have on the workforce. Some warm of staggering unemployment, but others point out that the technology may create new job categories that will employ these displaced workers. A third groups argues that the computers will have little effect on employment.

Decreased Work Force

In 2014, Google, valued at $370 billion, had only 55,000 employees which is just a tenth of the size of AT&T's workforce in the 1960's.

Current Use

Landing.ai, a startup formed by Andrew Ng, developed machine-vision tools that find microscopic defects in products at resolutions well beyond human vision. The machine-vision tools uses a machine-learning algorithm trained on small volumes of sample images. The computer not only "sees" the errors, but processes the information and learns from what it sees.

In 2014, China, Japan, the United States, the Republic of Korea and Germany together amounted to 70% of the total sales volume of robots. In the automotive industry, a sector with particularly high degree of automation, Japan had the highest density of industrial robots in the world: 1,414 per 10,000 employees.

Generative design, is a new process born from artificial intelligence. Designers or engineers input design goals- along with material parameters, manufacturing methods, and cost constraints- into generative design software. The software explores all potential permutations for a solution and generates design alternatives. The software uses machine learning to test and learn from each iteration what works and what doesn't. It's said to effectively rent 50,000 computers [in the cloud] for an hour.

Artificial intelligence is slowly become more commonplace in the modern world. AI personal assistants, like Siri or Alexa, have been around for military purposes since 2003.

Article Ideas

1. Habitat Fragmentation: Effect on Animal Behaviors
2. Radioactivity
3. Dana Angluin
4. Artificial Intelligence in the Heavy Industry : The gap is that all sights of "Artificial Intelligence in..." have a main page and this one doesn't. I want to create a main page for this and create a subset for the US and it's effects. I'm going to look at the other sights to see how they do their pages and base my research and what I should do on that. Haileywriter (talk) 00:27, 28 February 2019 (UTC)
5. AI for Good
6. Rendering (Animals)- Harmful and positive effects

COMMENT: These all sound interesting, but what are the gaps in these articles that you want to contribute? Please work on identifying those gaps and sources that you'll use before selecting one and assigning it to yourself. Julianfulton (talk) 04:54, 23 February 2019 (UTC)

Zuko: Article Evaluation

Everything is relevant to the character. The only thing that could use some improvement was the "Reception" section. It only showed the positive critiques and was very short. Nothing is out of date considering that the series already passed but the "Reception" should be updated and expanded. The positive perception is over-represented, but the tone is neutral. The links works. One of the sources was biased, it was a best characters list but a little bias is needed in the reception of the character category. The bias is noted in the section. The conversation is minimal. Only one person has posted on the Talk page. It is rated. It's a part of the Avatar project. It differs only because there's only one person on the Talk page. Though it does show how some parts can be in need of editing. I saw that from the "Reception" section. Haileywriter (talk) 03:52, 11 February 2019 (UTC)

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