Nola Palestrant, Tamalpais High School
Artificial Intelligence (A.I.) is a branch of computer science that was created in the 1950s. Unlike previous computer programs, A.I. allows machines to think and behave like humans without being explicitly programmed on their courses of action. A.I. strives to mimic humans’ reasoning, intelligence, decision-making, learning, and perception abilities. There are many complex techniques being used in A.I., including Neural Networks, Machine Learning, and Deep Learning. A.I. has been the subject of many controversies for its security with personal information, fairness, and misinformation, and has been vilified in numerous books and films. Regardless, Artificial Intelligence is becoming increasingly common in our modern world. Here are some ways we interact with it in our daily lives.
Music Recommendations
So many of us listen to music daily, and platforms like Spotify and Apple Music allow us to play the songs of our choosing at any moment. These services are so popular that they generate billions of dollars in revenue every year. The platforms couldn’t be the successful programs that they are without the use of Artificial Intelligence (A.I.).
Music platforms use A.I. for a variety of functions. A.I. provides personalized recommendations based on content the user frequently listens to. It’ll suggest what it predicts you’ll enjoy and avoid what you’ll dislike. Through reinforcement learning – which involves rewarding or punishing certain behaviors – these services will curate songs that are a good fit for you. Along the same lines, platforms will use A.I. to generate specific playlists based on your taste.
Music platforms use Natural Language Processing (which helps computers to understand text) and Deep Learning (a way of processing data similar to the human brain to link messages that are not explicitly stated) to enhance search capabilities. When you search for a song, you don’t need to write the title entirely correctly for the program to answer with what you want. A.I. will establish connections between the words you write and the content you intend to see.
As A.I. continues to grow, it will further transform the music industry. Currently, A.I. is revolutionizing production, breaking apart components of songs, and telling musicians which music will most satisfy their fans. As A.I. progresses, songs will be created entirely by A.I., underscoring the need and importance of musicians.
Virtual Assistants
Siri, Alexa, and Google Assistant were some of the first Artificial Intelligence (A.I.) to noticeably make its way into our homes. Released in 2011, 2014, and 2016, respectively, these devices revolutionized our interactions with technology.
The internet is no longer just at the tip of our fingers - it's at the tip of our tongues. With only a few words, users can know the weather next Tuesday, the directions to their favorite restaurant, or the complex workings of organic chemistry. Virtual Assistants allow tasks to be completed or questions to be answered hand-free and with ease.
Virtual Assistants like Siri, Alexa, and Google Assistant utilize a variety of algorithms to transform our words into data and then respond to its commands. This procedure, known as Natural Language Processing, or NLP, enables computers to understand words or text, thereby allowing conversation between technology and humans. Other programs such as Pattern Matching Algorithm (a sub-part of NLP) and Natural Language Generation (allows the A.I. 's response to be comprehensible and thorough) are examples of Artificial Intelligence techniques in these Virtual Assistants.
In combination with A.I., these technologies can evolve into more efficient and dependable machines, with the potential of further advancement. The algorithms Virtual Assistants run on are constantly advancing, and as the data used to run these programs is trained even further, its capabilities will continue to improve. In addition, recent A.I. like ChatGPT could be integrated with older ones, creating increasingly powerful Virtual Assistants.
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| Facial Recognition on personal devices |
Facial Recognition
Facial recognition, most commonly known for its use on phones, is an A.I. based technology that allows a person to be recognized despite never being seen in those same clothes, that same hair, or that same lighting. We use facial recognition (also called Face ID) to unlock our phones or purchase apps, but it can be used for anything pertaining to identity verification. Although we don't think much of it, facial recognition is a complex process.
The computer analyzes faces using their visual geometry, which is the relationship between different facial features. A.I. compares the data gathered from the original image to all the faces in the picture, finding the one that is a match. Deep learning processes enable faces to be transformed into numerical expressions. They are then used to look for similarities between the known person and the expressions of every other face.
In addition, A.I. is used in facial recognition to separate the subject from the landscape and objects in the background. Facial recognition can also be used in broader ways, such as in searching for lost people and finding criminals.
Currently, facial recognition is being developed to recognize when a person is lying. It does this by discerning subtle changes in facial expressions. As facial recognition becomes more precise and widely used, it can help prevent hacking personal items, as the only way to access the material is by being physically recognized as the owner. Facial recognition could be used to detect tiredness and other problems that may affect driving abilities, thereby reducing injuries.
Navigation
Navigation apps have become a critical part of modern transportation. Whenever we go to a new place, we no longer pull out a paper map; instead, our phones or cars direct us.
Immediately upon setting the destination, we are told of the traffic conditions, when we will arrive, and how long the journey will take us. And if you take a wrong turn - don’t worry! - the map will adjust your route automatically.
Artificial Intelligence (A.I.) is instrumental in making these features available. Using data from specific areas in the past few weeks, the map will analyze the likelihood and severity of traffic, giving the user an accurate ETA. In cases when traffic is high, A.I. suggests alternate routes to get you to your destination faster.
A.I. also takes into consideration road conditions, speed limits, and stop signs or lights. This allows it to decide the fastest route, not simply the shortest. It can also adjust to changes like road closures, crashes, or adverse weather.
This A.I. works using Graph Neural Networks, a program that can model changing data from the real world by translating it into graphs, and predict what will happen next time. It gathers this data through satellite imagery, crowdsourcing, user location data, and partnering with other companies.
In the future, A.I. could further analyze traffic data for common areas of traffic and accidents. This would enable navigation apps to route the user around such incidents before they occur. A.I. could also merge with satellites, combining data from things such as weather conditions and establishing routes more efficiently.
,_Point_Lobos_Avenue,_Autonomes_Auto_--_2022_--_112909%20(1).jpg) |
| Waymo, a Self-Driving Car Company, drives in San Fransisco |
Self-Driving Cars
Partially self-driving cars have risen to prominence over the last couple of decades, with the promises of reducing crashes by eliminating human error and expanding the accessibility of transportation. They “sense” their surrounding environment, aiming to adapt to and overcome any challenges, in order to control cars in the same way as humans.
The unpredictable and varying nature of human driving has inspired the development of self-driving cars, which rely on Artificial Intelligence (A.I.) to travel safely. Predictive modeling is the ability of A.I. to analyze patterns and anticipate future events. Predictive Modeling enables the car to anticipate the behavior of other cars and adjust to problems as they may arise. They use A.I. to make decisions in the moment, aiming to react to changes in their environment appropriately.
With the help of sensors feeding data to the computer, A.I. can recreate the car's surroundings. This allows it to recognize objects like crosswalks and traffic lights, and heed such signs correctly.
Many vehicles on the road today are already partially autonomous. Features including emergency braking and lane assistance are already widespread, with A.I. as an integral part of their success. These features have helped to keep drivers safe, and they will continue to improve.
Although completely self-driving cars are not yet commonly owned, if you live in a big city like San Francisco or Phoenix, you’re likely to see them being tested on the streets. Self-driving cars aren’t popular at the moment, but they could become much more common in the upcoming years, as products currently being tested are brought to market.
Works Cited
Artificial Intelligence (AI): What it is and why it matters. SAS. (n.d.). https://www.sas.com/en_us/insights/analytics/what-is-artificial-intelligence.html#:~:text=Artificial%20intelligence%20(AI)%20makes%20it,learning%20and%20natural%20language%20processing.
Dicker, R. (2021, May 18). A smoother ride and a more detailed map thanks to ai. Google. https://blog.google/products/maps/google-maps-101-ai-power-new-features-io-2021/
Frąckiewicz, M. (2023, March 10). The future of satellite navigation with AI and machine learning. TS2 SPACE. https://ts2.space/en/the-future-of-satellite-navigation-with-ai-and-machine-learning/
Kaput, M. (2022, September 19). How Spotify uses artificial intelligence-and what you can learn from it. Marketing AI Institute. https://www.marketingaiinstitute.com/blog/spotify-artificial-intelligence
Lau, J. (2020, September 3). Google maps 101: How ai helps predict traffic and determine routes. Google. https://blog.google/products/maps/google-maps-101-how-ai-helps-predict-traffic-and-determine-routes/
Lewis, J. A., & Crumpler, W. (n.d.). How does facial recognition work?. CSIS. https://www.csis.org/analysis/how-does-facial-recognition-work
A match made in transportation heaven: Ai and self-driving cars. Dataconomy. (2023, October 27). https://dataconomy.com/2022/12/28/artificial-intelligence-and-self-driving/
Self-driving cars explained. Union of Concerned Scientists. (n.d.). https://www.ucsusa.org/resources/self-driving-cars-101
What is natural language processing?. IBM. (n.d.). https://www.ibm.com/topics/natural-language-processing#:~:text=the%20next%20step-,What%20is%20natural%20language%20processing%3F,same%20way%20human%20beings%20can
Images:
File:San Francisco (CA, USA), point Lobos Avenue, autonomes auto ... (n.d.). https://commons.wikimedia.org/wiki/File:San_Francisco_%28CA%2C_USA%29%2C_Point_Lobos_Avenue%2C_Autonomes_Auto_--_2022_--_112909.jpg
MacKenzie, M. (2023, November 20). Facial recognition. Flickr. https://www.flickr.com/photos/mikemacmarketing/30188201497
Nola Palestrant, Tamalpais High School
Elic Weitzel is a human ecologist and archeologist at the University of Connecticut. He presented at Terra Linda’s Innovation Hub on October 25, 2023, to discuss his research with pre- and post-colonial White-Tailed Deer herds, and what their fluctuating populations can tell us about how the humans living in New England interacted with the environment. Following the arrival of Europeans, White-Tailed Deer populations decreased from 30 million to 300,000. This decline was largely a result of a decreased Native American population - which had previously performed control burns that optimized the environment for deer - and an increase in commodification. Mr. Weitzel’s research can be used as a foundation for us to reconsider our interactions with the natural world, with the ultimate goal of promoting sustainability.
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| Elic Weitzel |
2. What are some things that people can notice about the world around them that provide clues into the past?
Most material clues into the past are invisible, as they're often buried in the ground, but we definitely take for granted all the ways in which the past can still be visible to us today, in one form or another. The names of the roads that we drive on are my favorite example of this. These often offer clues into what the landscape used to be like, recorded in names such as Indian Village Road, Old Mine Road, etc. Most people don't think twice about these sorts of things, but these place names are often a clue that there used to be a Native village or historical gold mine in the area. Some other clues require a closer look to interpret. For example, archaeologists have found that the plant species that grow around ancient archaeological sites are often different from the species which grow elsewhere. This is because people long ago modified the landscape around where they lived, either deliberately or inadvertently, and that legacy continues to shape today's ecosystems. Finally, you can sometimes find archaeological artifacts like arrowheads or pottery if you know what you're looking for. They often turn up in many different places since people have lived on the land for so many thousands of years. It's never good to take an artifact if you do find one, as removing artifacts from their context prevents archaeologists from learning anything about the past through them. But they do exist out there and many people accidentally encounter them.
3. What materials have been commodified by past societies that could increase our sustainability if we lessen their values?
Most past societies never commodified anything. The process of taking something and exchanging it in a market economy to make money is a very recent development in human history. One can make an argument that certain societies in the past like the Romans may have engaged in a form of this activity, but the way that commodities are produced and exchanged in our world today only dates back around 500 years to the birth of capitalism in northwestern Europe. As such, most societies throughout time would likely have found such a behavior to be quite strange, and would be especially shocked at how such an economy functions. I certainly think the evidence suggests that commodification of natural resources and people's labor has led to a wide variety of problems in the world today, so I too find such a behavior to be quite strange. But regardless of what is being commodified and when, the key to promoting sustainability is to focus on meeting people's needs, not on making money. That's the trick to reducing the value of a commodity back to a more reasonable level: strip away the extra value it has to those despotic individuals in society engaged in exploitation and profiteering and get back to the basics of helping all people survive and thrive. For example, water has very high value to everyone since it's necessary for survival. But certain individuals and corporations often try to control water, prevent others from accessing it, and then charge high prices for access: essentially selling the water back to the people who live on top of it. Nestle has recently done this in California, sucking up all the groundwater reserves in certain areas to make money from bottled water sales. Archaeologists have found that in the past, many societies had very elaborate systems of managing water at the local community level. A lot of this research even comes from the southwestern United States. These systems of water management ensured that everyone could access water and that it remained sustainably available into the future. So the way to prevent despotic individuals and groups from artificially inflating the value of commodified resources is to prevent them from gaining control in the first place. I think the archaeological evidence suggests that the best way to do that is through strong, local democratic control of resources by relevant stakeholders.
4. What practices from pre-colonial Native Americans can we replicate today to create a more sustainable society?
In general, I wouldn't argue that we need to adopt practices from any past societies to promote sustainability in the present. I think the social, economic, and political contexts in which people used to live are not analogous to those we find ourselves in today, so many specific practices likely wouldn't transfer well. Sometimes something specific could be adopted, such as controlled burning of the landscape to promote ecosystem health. But I think more generally, we can be inspired to develop new sustainable practices by studying old ones. There is abundant evidence, for example, that sustainability in the past often occurred when groups of people managed natural resources and economic systems themselves on a local level. Outcomes were often unsustainable when outside groups of despotic individuals sought to control the resources, labor, and bodies of others for their own benefit. So based on that, I think the biggest thing that we can do today to promote sustainability is to implement stronger democratic control of the economy on a local level. Keeping things local means that people have a vested interest in sustainability since it directly impacts them, and keeping things democratic ensures that those stakeholders can govern their own lives and their own communities and prevent any selfish individuals from exploiting the group for personal gain. I don't think that we need to directly adopt a way of doing this from a thousand years ago, but the general principle remains the same: local democracy by stakeholders leads to far better outcomes for people and nature. As such, if we really want a sustainable society today, I think we need to take that lesson and implement it however we can in our own historical context. So, inspired by my research and that of others, I think worker co-ops, land trusts, and other forms of community governance are our best options to promote a sustainable future. These aren't things that past societies did specifically, but the general principles behind such practices were implemented to great success in the past and would likely be successful in the present as well.
5. What other peoples or practices from the past would you like to research that could provide insight to aid our efforts to live more sustainably?
The big question for me is how sustainability follows from economic governance and control. I want to keep investigating all the different ways that local democracy by the relevant stakeholders contributes to a sustainable economy. I think unsustainability often results from self-interested individuals in society attempting to become despots and control the economy for their own benefit. This then leads to overuse of resources and exploitation of other people. So I'd really like to keep exploring how these processes worked in the past in the hopes that I can learn more about sustainability and implement helpful policies in the present. For example, some societies in the past were remarkably egalitarian for their size and complexity, like the ancient Bronze Age state that existed in present-day India and Pakistan called the Harappan or Indus Valley civilization. It would be fascinating to study such a context to see whether a less hierarchical and potentially more democratic society was indeed more sustainable. I also think that many smaller-scale societies are useful to study, especially tribal societies like the Amazigh of northern Africa or pre-20th century Albanian tribes, as these groups often had sophisticated ways of governing resource use and economics on a local level. While restructuring 21st century America into a tribal society would not be useful or viable, that doesn't mean that tribal groups don't have lessons to teach us in how a community can sustainably exist in their environment for millennia.
By Sahiti Namburu, Terra Linda High School After going to the Marine Wildlife off our Coasts: Studying Sea birds, Marine Mammals and More ...
