Theme 1 - Algorithms will continue to spread everywhere

Algorithms are everywhere around us. It does not have to be using some technology. Jim Warren, a technologist and entrepreneur describes an algorithm as “Any sequence of instructions for how to do something (or how a machine that can understand said instructions can do it) is – by definition – an algorithm.” (Rainie & Anderson, 2017, p.2). Throughout history, we have been using algorithms for many reasons built on various situations. It has advanced our abilities and molded our society into what it is now. Algorithms are integrated into everything we do today and in all services we use. Therefore, algorithms are more prevalent than ever in this technology era and in our everyday lives. There is no stopping its growth.

Algorithms in our daily lives

Every action that one performs is done in a sequence of steps. As with any task, we find ways to do them faster. The steps are simplified to make the process of completing a task more efficient. This is the center of our need for using algorithms in technology - our need to improve. To some degree, all services used today are automated to make processes efficient. Whether it be entertainment, health care, protection, transportation, etc. Now we can’t tell the difference between a bank processing a transaction or the teller in the bank you spoke to processing your transfer(Rainie & Anderson, 2017).

Algorithms in different areas of study

Members of the ACM group receive weekly emails regarding how technology has been a tool to address issues, evolve research, and predict future outcomes in many areas of study. Such developments amplify the influence of algorithms(Rainie & Anderson, 2017). Without algorithms, we can’t do anything useful. We won’t solve complex problems or advance our technology or our knowledge. With that said, it is incredibly important that the use of algorithms spreads as it is currently.

Theme 2 - Good things ahead

Algorithms make us happy and leave us in awe of its capabilities

It is observed that algorithms do the heavy lifting. Therefore, we can focus more on what is important - the results from the algorithms. Also, this allows us to focus our time on other positive things. For example, the astrophysicist Dr. Becky Smethurst, in her Youtube video, came to work to discover that her algorithm, which ”tries to find the best model of the star formation history in a galaxy given the light that we observe from it”(Smethurst, 2019) had finished.

We know that machine learning involves training our algorithms to perform tasks on their own. In high-risk situations, an algorithm is best accompanied by a person cross-checking performance and results. With this said, I see algorithms being used as a tool by professionals to enhance their work output(especially us future engineers).

What struck me a lot in 2016 was the robot “Sophia” that Hanson Robotics had unfortunately decommissioned and the game “Detroit: Become Human.” At the time, Sophia had attained citizenship and was part of a project that aimed to better human-robot interaction on a personal level (Hanson Robotics, 2020). On the other hand, in the video game, gamers saw a life where these humanoid robots labor for us and even empathize. As scary as this may be, it is becoming a reality as AI, machine learning, and other technological fields advance. The measure of how good this will be, in my opinion, is difficult.

Algorithms as an extension of ourselves

Lastly, I think that future algorithms will become closer to humans. It will become part of our being and make our basic actions more efficient. For example, many YouTube fans of the “Onewheel” have expressed that the electronic skateboard feels like an extension of themself; simply thinking where they want to go, and the gadget listens. Another example is Elon musk’s Neuralink, where he strides toward his final goal of fabricating a connection between human minds and AI(Hamilton, 2022).

Algorithms in industry

Organizations utilize algorithms to process large volumes of data and return insightful information that can then be acted upon to satisfy clients. Inversely, some algorithms can model some aspect of their service and make their own decisions. For example, in social media, most of the videos in our feed are selected via an algorithm rather than having to visit hashtags(Rainie & Anderson, 2017). Many individuals have even learned to use it to gain views, likes, and fame fairly quickly. We have learned in software engineering and algorithms class that in dependable systems, refining the software behind them is mandatory. It is important that these algorithms minimize errors, be autonomous, and interact with algorithms from other systems. Consequently, we can be reassured that ahead lies efficient algorithms in our most high-risk and reliant systems.

There are even algorithms made to evaluate other algorithms. Thus, as we continue, we are sure that the efficiency of current algorithms will grow. In addition, the ethics of algorithmic decision-making is already being considered(Rainie & Anderson, 2017).

Theme 3 - Humanity and Human Judgement are lost when data and predictive modeling become paramount.

Companies worldwide have figured out ways to automate different things in our lives and market them to us. Tech giants and other profit organizations have one goal in mind, and that is to innovate their profit machines. It is important to mention that computers are stupid. They follow the software instructions as is, no matter what. Therefore, algorithms are not biased; their creators might inadvertently create them with bias. As we move into the future, organizations might opt out of choosing complex algorithms that can benefit the individual(Rainie, 2022). Rather, they will find simpler solutions that influence our decisions and time using their service to make revenue. I can say that there is bias in profit organizations for the current state of affairs. In the future, as our algorithms evolve, these companies will continue down this path of not favoring users but their own agendas.

Regarding agendas, algorithms are even being used to manipulate societies. It should be known that TikTok users in China do not see the same content as the western world. An explanation could be due to cultural reasons. Another major reason is that the government highly regulates social media content. Here, we can see an example of the future of algorithms being used for manipulation. Another obvious example is google showing us ads based on things we watched, searched, or even stated. This behavioral data is captured and used in an effort to influence possible future purchases.

My hot take is that an algorithm does not evolve to dehumanize us. Rather, the creators or elites of organizations allow their algorithms to treat us as pawns in their agendas.

There is a dull line between complex algorithms and our understanding of how they come to conclusions based on data and patterns of our behavior - even for the algorithms’ creators. Our reliance on and ignorance of algorithms diminishes our creativity and critical thinking skills. In the most recent news, ChatGPT is being used by students to cheat. This is just a small instance of where algorithms work for us while we gain no real understanding. I’ve recently been recommended a video where YouTuber ForrestKnight talks about gaining an understanding through asking relative questions of the work to ChatGPT. If we don’t think like this now, our inability to come to our own conclusions for ourselves in a future of even more powerful algorithms is scary. Its benefits may seem attractive, but there is an underlying danger when putting too much trust in these algorithms. Who is to blame when things go wrong?

References

Dr. Becky. (2019). A day in the life of an Astrophysicist at Oxford University. YouTube. Retrieved from https://www.youtube.com/watch?v=XW_qIqLhPkI&t=448s.

ForrestKnight. (2023). If you use ChatGPT to CHEAT, do this ONE THING! Retrieved from https://www.youtube.com/watch?v=Xffgj-RjOXw.

Hamilton, I. A. (2022, December 3). The story of Neuralink: Elon Musk's AI brain-chip company where he had twins with a top executive. Business Insider. Retrieved from https://www.businessinsider.com/neuralink-elon-musk-microchips-brains-ai-2021-2

Rainie, L. (2022, September 15). Theme 3: Humanity and human judgment are lost when data and predictive modeling become Paramount. Pew Research Center: Internet, Science & Tech. Retrieved from https://www.pewresearch.org/internet/2017/02/08/theme-3-humanity-and-human-judgment-are-lost-when-data-and-predictive-modeling-become-paramount/#some-fear-people-could-lose-sophisticated-decision-making-capabilities-and-local-intelligence

Rainie, L., & Anderson, J. (2017, February 8). Theme 1: Algorithms will continue to spread everywhere. Pew Research Center: Internet, Science & Tech. Retrieved from https://www.pewresearch.org/internet/2017/02/08/theme-1-algorithms-will-continue-to-spread-everywhere/

Rainie, L., & Anderson, J. (2017, February 8). Theme 2: Good things lie ahead. Pew Research Center: Internet, Science & Tech. Retrieved from https://www.pewresearch.org/internet/2017/02/08/theme-2-good-things-lie-ahead/

Sophia. Hanson Robotics. (2020, September 1). Retrieved from https://www.hansonrobotics.com/sophia/