Author: Shaashvat

In our history classes we have learned that during the 20th century, the Industrial Revolution had a great impact on American and global societies. The mass production of goods allowed America to trade more efficiently with European countries which boosted the American economy. But there was a backlash to this new technology; skilled workers and craftsmen saw this new technology, which could be easily used by ordinary people, as a threat to their businesses. The modern age brings a new technology—Artificial Intelligence (AI). The advent of AI is beneficial for society, but it’s important to take into consideration its negative implications so we can come to ethical conclusions. Why might some be against AI?

One of the major negative impacts of AI includes how it might impact society. “…AI-driven technologies have a pattern of entrenching social divides and exacerbating social inequality, particularly among historically marginalized groups” (Hagerty and Rubinov). Because AI models train from data sets that could be biased (not diverse enough), it could potentially create further divides among social groups. Many civilians might consider these issues to be a major threat that comes with AI. Beyond the economic sphere, the possibilities of AI are being explored in Healthcare. New Healthcare systems are being developed to help doctors with their medical processes and evaluations. But this new AI can be biased thus leading to harmful results for the patient. “…algorithms trained with gender-imbalanced data do worse at reading chest x-rays for an underrepresented gender…”(Kaushal and Altman and Langlotz). Because these AI models are trained on data that is biased it could lead to false-positive or false negatives for specific groups. This could be potentially fatal for patients. For example, if a patient is believed to have cancer, but they actually don’t, this false positive could make them go through chemotherapy which is dangerous. Likewise, if a patient has cancer which the model doesn’t detect this would mean that the patient would be left untreated. Issues of biased data also extend into the legal system.  In the legal system, AI is being used to help lawyers with court decisions. But the biased data sets lead to unfair rulings being made. “ Using COMPAS, Black defendants were incorrectly labeled as “high-risk” to commit a future crime twice as often as their white counterparts” (Mesa). For these reasons, groups–especially underrepresented groups–may feel threatened by AI because of the biased data. Regardless of these reasons, AI is being improved and developed to fix such issues and promises a safer future for us.

AI promises beneficial technology. Even though many may argue that AI is bad for the environment because of the metric tons of carbon dioxide it emits into the atmosphere (during the training process), the long-term effects seem to far outweigh the negatives. “It can also underpin low-carbon systems, for instance, by supporting the creation of circular economies and smart cities that efficiently use their resources”(The Role of Artificial Intelligence in Achieving the Sustainable Development Goals). AI could actually help cities use energy more efficiently which is better for the environment. The Vice President of Manifold (An AI Company), Rajendra Koppula, said that in the short term AI might be creating more harm to the environment, but in the long run, it may be more beneficial. AI is also being utilized in the legal system to help lawyers make decisions and resolve disputes. “ some offer litigation analytical tools that analyze precedent case data and other data to aid lawyers in predicting case outcomes”(AI in legal services: new trends in AI-enabled legal services). With AI, lawyers could potentially help more people because they would be able to go through court cases faster. Even though some may argue that AI is detrimental if it’s implemented in health care systems, it does promise benefits. “Experts predict AI to have a significant impact in diverse areas of healthcare such as chronic disease management and clinical decision making”(Ahuja). AI could help doctors in various fields of healthcare. For example, AI is being used to help radiologists analyze images. Thus helping them save time to help other patients or even get more accurate results. AI won’t replace doctors but rather improve their jobs (Koppula). 

Now because there are plausible explanations as to whether or not AI really poses a threat to society, we must come to a common ground as to what is considered ethical or unethical. For example, even though AI is believed to help lawyers make legal decisions, Koppula and I agree that AI shouldn’t be used in the legal system. Morally this is wrong because the predictions by these models have been greatly biased. “You should not try to replace a judge, or some legal proceeding simply because now you have a model that is trained on historical cases…far more moral and ethical to not jump the gun (Koppula).” Since court systems are very important to uphold the rights of citizens, it would be morally incorrect to use a biased system to decide whether or not someone is guilty or innocent. This is why more research should be done as to the impacts that these AI models would have on society so that such issues would be resolved before they happened. Creating these AI systems is very mind-numbing in the sense that it is difficult to decide what is considered ethical or unethical. One prevalent use of AI is in self-driving cars. Those who are in favor of Self Driving cars claim that they drive safer than humans which would result in fewer accidents and more lives being saved. But Self Driving cars bring controversy,“For instance, should autonomous vehicles be programmed to always minimize the number of deaths? Or should they perhaps be programmed to save their passengers at all costs (Nyholm and Smids)?” It may be unsettling to think that your self-driving car might sacrifice your life and the lives of your passengers in order to save more people overall. This is why it has created more ethical dilemmas. Even though AI brings lots of promise to help society, there are still some more questions that need to be asked as to the impacts it brings.

Ahuja, Abhimanyu S. “The Impact of Artificial Intelligence in Medicine on the Future Role of the Physician.” PeerJ, 4 Oct. 2019, https://peerj.com/articles/7702/. 

Hagerty, Alexa, and Igor Rubinov. Global AI Ethics: A Review of the Social Impacts … – Arxiv. https://arxiv.org/pdf/1907.07892.pdf. 

Kauffman, Marcos Eduardo, and Marcelo Negri Soares. “Ai in Legal Services: New Trends in AI-Enabled Legal Services – Service Oriented Computing and Applications.” SpringerLink, Springer London, 18 Oct. 2020, https://link.springer.com/article/10.1007/s11761-020-00305-x. 

Kaushal, Amit, et al. Health Care AI Systems Are Biased. 17 Nov. 2020, https://fully-human.org/wp-content/uploads/2021/01/Health-Care-AI-Systems-Are-Biased.pdf.

Nyholm, Sven, and Jilles Smids. “The Ethics of Accident-Algorithms for Self-Driving Cars: An Applied Trolley Problem? – Ethical Theory and Moral Practice.” SpringerLink, Springer Netherlands, 28 July 2016, https://link.springer.com/article/10.1007/s10677-016-9745-2. 

Mesa, Natalia. “Can the Criminal Justice System’s Artificial Intelligence Ever Be Truly Fair?” Massive Science, 13 May 2021, https://massivesci.com/articles/machine-learning-compas-racism-policing-fairness/. 

Vinuesa, Ricardo, et al. “The Role of Artificial Intelligence in Achieving the Sustainable Development Goals.” Nature News, Nature Publishing Group, 13 Jan. 2020, https://www.nature.com/articles/s41467-019-14108-y. 

I play chess competitively and have managed to get my rating up to 1700 on chess.com in rapid. Here is my essay on chess where I talk about how to improve your skills at this game.

How to Get Better At Chess

I believe that chess is a game unlike any other because it teaches us various skills that pertain to the real world. Instead of thinking from just our perspective, chess teaches us to see the advantages and disadvantages in our position as well as in our opponents. It develops our strategical thinking, allowing us to deduce various positions and find the one that will be most successful. Chess improves our memorization skills through remembering certain checkmate patterns, openings, or even being able to visualize how a position will be 20 moves ahead. As you get better at chess, these skills will also improve. This is why in addition to playing chess, it is important to learn how to get better at it.

There are three stages in a chess game, the opening, middle game, and endgame. Many beginners after learning how to move the chess pieces dive right into learning opening theory which is the various different ways of starting a chess game and memorizing a series of moves in that opening. Even though it may seem conspicuous to start with the opening theory, this is a big blunder. Chess is more than just memorizing a bunch of moves to play against your opponent; it is also about being intuitive, using your reasoning skills and knowledge to make the correct moves. The opening theory will be completely useless when you get into the middle game and the end game because you will no longer be part of the opening. This is why it is important to practice puzzles first. You can do this by buying a chess book with puzzles or even buying a membership to a chess site that gives puzzles. These puzzles are very critical in your journey to improving at chess because you will be enhancing your perspective and strategical skills. In order to get better at anything, practice is key. Similarly, play many chess games, but review the game afterward using a chess engine. This is so that you learn from your mistakes and learn why you need to play a different move next time you reach a similar situation. Regardless if you won or lost the game, you can learn a lot from analyzing it. After practicing puzzles, then get into memorization. However, don’t memorize openings yet, but instead, memorize checkmate patterns or important positional strategies. Most of a chess game happens in the middle game and the endgame which is why you first develop these strategies first. 

After learning from puzzles, and other strategies, now study openings more intensively. Remember, the number one key in chess is to control the center of the chessboard. If you control the center, you control the game. The Queen is the most powerful piece on the chessboard, but don’t bring it out very early on in the game. This is because as your opponent is developing their pieces, these pieces could attack your Queen; this will force your Queen to return thus giving your opponent a tempo. A tempo in chess is basically a free move, in the process of retreating a piece, your opponent will be getting a free move allowing them to control the center more. When just starting chess, you will notice that most opponents will play the classic e4 e5 openings (the two front pawns moving 2 squares up). This is a very classic opening that the famous Bobby Fischer, one of the greatest legends of chess used to play all the time because it effectively controls the center at the very beginning of the game. But the reason why I don’t like to play this classic opening is that it is a very familiar opening that you will see a thousand times. If you really want to surprise your opponent and take them to unfamiliar territory, play something unique. This is where gambits come into place. A gambit is where an opponent will sacrifice a pawn or two or even a minor piece (a bishop or a knight) in order to get a future positional advantage. My favorite chess opening is the Danish Gambit, it is known to be the most aggressive chess opening that tends to confuse my opponents, especially those who have never seen it before. Other good openings to learn are the Queen’s Gambit, French Defense, and Caro Kann. There are hundreds of different chess openings, each with many variations. Don’t overwhelm yourself by learning as many chess openings as you can though. Finding the ones that you are the most successful with and continuing to improve them through experimentation and learning from computer analysis is a good method in getting better at chess. After getting out of the opening, this is where your middle game and end game skills come into play.