<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.10.0">Jekyll</generator><link href="https://hefnereb.github.io/feed.xml" rel="self" type="application/atom+xml" /><link href="https://hefnereb.github.io/" rel="alternate" type="text/html" /><updated>2026-04-13T20:51:32+00:00</updated><id>https://hefnereb.github.io/feed.xml</id><title type="html">My CS 4100 Blog</title><subtitle>Short blog I put together for my Senior Seminar Class.</subtitle><author><name>Eli Hefner</name></author><entry><title type="html">Fifth Blog Post: Reflection On Ai</title><link href="https://hefnereb.github.io/2026/03/31/Fifth-Blog-Post-Reflection-On-AI.html" rel="alternate" type="text/html" title="Fifth Blog Post: Reflection On Ai" /><published>2026-03-31T00:00:00+00:00</published><updated>2026-03-31T00:00:00+00:00</updated><id>https://hefnereb.github.io/2026/03/31/Fifth-Blog-Post:-Reflection-On-AI</id><content type="html" xml:base="https://hefnereb.github.io/2026/03/31/Fifth-Blog-Post-Reflection-On-AI.html"><![CDATA[<p>Generative AI already has some clear downsides, especially its environmental cost and the way it is being pushed into so many parts of life so quickly, including areas where it probably does not belong. In many cases, there seems to be very little concern for the long-term effects, and it feels like we are in an arms race to develop the most sophisticated and efficient AI possible. It can also make people too dependent on it, replacing parts of thinking, creating, and problem-solving that should still matter. Even with those concerns, I am still excited about its potential, especially as someone going into tech. I think it would be a mistake not to learn how to use it, because AI is clearly going to remain an important part of the field. What interests me most is how it can help people learn new technologies faster and speed up development when it is used properly. Instead of spending as much time stuck on small repetitive tasks or taking too long to ramp up on unfamiliar tools, AI can help accelerate that process and let people focus more on higher-level ideas, creativity, and decision-making. That is the side of it that feels most exciting to me: not just using AI as a shortcut, but using it as a tool that can make learning and building faster and more effective when it is guided well.</p>]]></content><author><name>Eli Hefner</name></author><category term="Other" /><summary type="html"><![CDATA[Generative AI already has some clear downsides, especially its environmental cost and the way it is being pushed into so many parts of life so quickly, including areas where it probably does not belong. In many cases, there seems to be very little concern for the long-term effects, and it feels like we are in an arms race to develop the most sophisticated and efficient AI possible. It can also make people too dependent on it, replacing parts of thinking, creating, and problem-solving that should still matter. Even with those concerns, I am still excited about its potential, especially as someone going into tech. I think it would be a mistake not to learn how to use it, because AI is clearly going to remain an important part of the field. What interests me most is how it can help people learn new technologies faster and speed up development when it is used properly. Instead of spending as much time stuck on small repetitive tasks or taking too long to ramp up on unfamiliar tools, AI can help accelerate that process and let people focus more on higher-level ideas, creativity, and decision-making. That is the side of it that feels most exciting to me: not just using AI as a shortcut, but using it as a tool that can make learning and building faster and more effective when it is guided well.]]></summary></entry><entry><title type="html">Fourth Blog Post: Reflection On Privacy</title><link href="https://hefnereb.github.io/2026/03/17/Fourth-Blog-Post-Reflection-On-Privacy.html" rel="alternate" type="text/html" title="Fourth Blog Post: Reflection On Privacy" /><published>2026-03-17T00:00:00+00:00</published><updated>2026-03-17T00:00:00+00:00</updated><id>https://hefnereb.github.io/2026/03/17/Fourth-Blog-Post:-Reflection-On-Privacy</id><content type="html" xml:base="https://hefnereb.github.io/2026/03/17/Fourth-Blog-Post-Reflection-On-Privacy.html"><![CDATA[<p>For the “What Did You Find” assignment, I found about what I expected. I was already aware that it is pretty easy to find basic information about people online if you know where to look. With enough searching, I could find things like an address, phone number, political party affiliation, and even some high school sports records. None of that was especially shocking to me, because I feel like most of us already know that a lot of personal information is out there and not that hard to access.</p>

<p>What surprised me more was not the personal information itself, but the amount of surveillance that exists in everyday life now. Some of it is expected, like security cameras in stores, parking lots, and public places. But there are also less obvious forms of surveillance, like Flock cameras and Ring cameras, that make it feel like we are being watched almost everywhere we go. Even if nobody is actively paying attention all the time, the fact that so much can be recorded and stored changes the way privacy feels.</p>

<p>It is also interesting, and a little concerning, that AI tools are being developed to make even more use of all this collected data and video. It is not just that footage is being recorded anymore, but that new systems can analyze it, sort through it, and draw conclusions from it much faster than a person could. That makes the whole issue feel bigger, because the amount of surveillance is growing, but so is the ability to actually use that information in powerful ways.</p>

<p>That constant sense of being watched also affects how people act. It seems like people are more careful, more filtered, and sometimes less willing to be themselves because anything can be recorded, shared, and judged later. Overall, this assignment mostly confirmed what I already believed about how much information is available online, but it also made me think more about how normal surveillance has become in everyday life.</p>]]></content><author><name>Eli Hefner</name></author><category term="Other" /><summary type="html"><![CDATA[For the “What Did You Find” assignment, I found about what I expected. I was already aware that it is pretty easy to find basic information about people online if you know where to look. With enough searching, I could find things like an address, phone number, political party affiliation, and even some high school sports records. None of that was especially shocking to me, because I feel like most of us already know that a lot of personal information is out there and not that hard to access.]]></summary></entry><entry><title type="html">Third Blog Post: Reflection On Citizenfour</title><link href="https://hefnereb.github.io/2026/02/25/Third-Blog-Post-Reflection-On-Citizenfour.html" rel="alternate" type="text/html" title="Third Blog Post: Reflection On Citizenfour" /><published>2026-02-25T00:00:00+00:00</published><updated>2026-02-25T00:00:00+00:00</updated><id>https://hefnereb.github.io/2026/02/25/Third-Blog-Post:-Reflection-On-Citizenfour</id><content type="html" xml:base="https://hefnereb.github.io/2026/02/25/Third-Blog-Post-Reflection-On-Citizenfour.html"><![CDATA[<p>Watching Citizenfour honestly made everything feel way more real than just reading about the effect Edward Snowden had like I had done previously. Seeing him in that hotel room in Hong Kong calmly explaining why he leaked the documents made it clear that this was not some impulsive act, it was something he thought deeply about and knew would change his life forever. The biggest takeaway for me is how massive and normalized government surveillance had become without most people even realizing it, especially under programs justified by national security. It was surprising how much data was being collected from ordinary people who were not suspected of any crimes, and I was also surprised at the level of surveillance that still goes on in the UK and how closely allied countries cooperate in sharing intelligence. It is also crazy to me that he still has not been pardoned and continues to live in exile years later. The documentary really made me think about the tradeoff between security and privacy, and how easily fear can be used to expand government power. More than anything, it showed how one person’s decision can spark a global conversation about transparency, accountability, and digital rights.</p>]]></content><author><name>Eli Hefner</name></author><category term="Other" /><summary type="html"><![CDATA[Watching Citizenfour honestly made everything feel way more real than just reading about the effect Edward Snowden had like I had done previously. Seeing him in that hotel room in Hong Kong calmly explaining why he leaked the documents made it clear that this was not some impulsive act, it was something he thought deeply about and knew would change his life forever. The biggest takeaway for me is how massive and normalized government surveillance had become without most people even realizing it, especially under programs justified by national security. It was surprising how much data was being collected from ordinary people who were not suspected of any crimes, and I was also surprised at the level of surveillance that still goes on in the UK and how closely allied countries cooperate in sharing intelligence. It is also crazy to me that he still has not been pardoned and continues to live in exile years later. The documentary really made me think about the tradeoff between security and privacy, and how easily fear can be used to expand government power. More than anything, it showed how one person’s decision can spark a global conversation about transparency, accountability, and digital rights.]]></summary></entry><entry><title type="html">Second Blog Post: Reflection On Hive Tracks &amp;amp; Bee Informed Partnership</title><link href="https://hefnereb.github.io/2026/02/16/Second-Blog-Post-Reflection-On-Hive-Tracks-&-Bee-Informed-Partnership.html" rel="alternate" type="text/html" title="Second Blog Post: Reflection On Hive Tracks &amp;amp; Bee Informed Partnership" /><published>2026-02-16T00:00:00+00:00</published><updated>2026-02-16T00:00:00+00:00</updated><id>https://hefnereb.github.io/2026/02/16/Second-Blog-Post:-Reflection-On-Hive-Tracks-&amp;-Bee-Informed-Partnership</id><content type="html" xml:base="https://hefnereb.github.io/2026/02/16/Second-Blog-Post-Reflection-On-Hive-Tracks-&amp;-Bee-Informed-Partnership.html"><![CDATA[<p>After the Hive Tracks and Bee Informed Partnership discussion, I learned three main things. First, I learned just how important bees are to agriculture, especially in large-scale crops like almonds in California. I did not realize how dependent certain industries are on managed bee colonies for pollination, and how major losses in bee populations can directly affect food production and the economy. Second, I learned more about code ownership and how complicated it can become. The case made it clear that code you write is generally yours, but that can change depending on contracts, employment agreements, and funding sources. When organizations and money are involved, ownership and control over software become serious ethical and legal issues. Third, I learned how sensitive user and research data can be managed by third parties, but that responsibility does not disappear just because another company stores or processes the data. There is still an ethical obligation to protect users and clearly define who has access to what.</p>]]></content><author><name>Eli Hefner</name></author><category term="Other" /><summary type="html"><![CDATA[After the Hive Tracks and Bee Informed Partnership discussion, I learned three main things. First, I learned just how important bees are to agriculture, especially in large-scale crops like almonds in California. I did not realize how dependent certain industries are on managed bee colonies for pollination, and how major losses in bee populations can directly affect food production and the economy. Second, I learned more about code ownership and how complicated it can become. The case made it clear that code you write is generally yours, but that can change depending on contracts, employment agreements, and funding sources. When organizations and money are involved, ownership and control over software become serious ethical and legal issues. Third, I learned how sensitive user and research data can be managed by third parties, but that responsibility does not disappear just because another company stores or processes the data. There is still an ethical obligation to protect users and clearly define who has access to what.]]></summary></entry><entry><title type="html">First Blog Post: Best Computing Experiences</title><link href="https://hefnereb.github.io/2026/01/15/First-Blog-Post-Best-Computing-Experiences.html" rel="alternate" type="text/html" title="First Blog Post: Best Computing Experiences" /><published>2026-01-15T00:00:00+00:00</published><updated>2026-01-15T00:00:00+00:00</updated><id>https://hefnereb.github.io/2026/01/15/First-Blog-Post:-Best-Computing-Experiences</id><content type="html" xml:base="https://hefnereb.github.io/2026/01/15/First-Blog-Post-Best-Computing-Experiences.html"><![CDATA[<p>The best in-class coding experience I’ve had was in Programming Analysis, which I took over the summer. In that course, I worked on writing an extension to Google’s Error Prone static analysis tool. My extension scanned Java codebases and flagged the use of “magic number” literals, encouraging developers to replace them with named constants for improved readability and maintainability. Each of us independently extended a different part of the checker, which allowed us to work autonomously and dive deeply into our own implementation challenges. Later, we brought our work together and presented our individual components so they could be merged into a single, cohesive tool. I especially enjoyed this structure because it mirrored real-world collaborative development: independent contributions that ultimately combined to produce a meaningful, shared improvement.</p>

<p>My best out of class coding experience was building a personal website. Going into the project, I had little to no experience with web development, so learning HTML, CSS, and JavaScript entirely on my own out of class was very refreshing. Without the pressure of deadlines or grades, I found the process extremely relaxing and engaging and being able to immediately see the visual results made the learning experience very rewarding.</p>

<hr />]]></content><author><name>Eli Hefner</name></author><category term="Other" /><summary type="html"><![CDATA[The best in-class coding experience I’ve had was in Programming Analysis, which I took over the summer. In that course, I worked on writing an extension to Google’s Error Prone static analysis tool. My extension scanned Java codebases and flagged the use of “magic number” literals, encouraging developers to replace them with named constants for improved readability and maintainability. Each of us independently extended a different part of the checker, which allowed us to work autonomously and dive deeply into our own implementation challenges. Later, we brought our work together and presented our individual components so they could be merged into a single, cohesive tool. I especially enjoyed this structure because it mirrored real-world collaborative development: independent contributions that ultimately combined to produce a meaningful, shared improvement.]]></summary></entry></feed>