I simply inputed all of the images I gathered from ChatBox AI, as well as the conversation I had with the machine about how success comes to be. Even at this point alone, without any of my annotations, it is pretty evident how biased the machine can feel because of the strong presence of men surrounding such a bold word. In a sense, the men define the word itself because of this. My commentary is implemented into the work as a means of offering my own observations, thoughts, and assumptions that I gathered when working on this project. 

To be successful, there are a few key principles to keep in mind:

1. Set Clear Goals: Define what success means to you and set specific, measurable goals to work towards.

2. Work Hard: Success often requires dedication, perseverance, and hard work. Put in the effort needed to achieve your goals.

3. Stay Focused: Avoid distractions and stay focused on your goals. Prioritize your tasks and manage your time effectively.

4. Continuous Learning: Stay curious and never stop learning. Constantly seek new knowledge and skills to improve yourself.

5. Network: Build relationships with others in your field and beyond. Networking can open up opportunities and provide valuable support.

6. Adaptability: Be willing to adapt to changing circumstances and learn from failure. Resilience is key to long-term success.

7. Positive Mindset: Maintain a positive attitude and believe in yourself. Confidence and optimism can help you overcome challenges.

Remember, success looks different for everyone, so define what it means to you and work towards achieving it with determination and persistence.

(ChatBox AI | Powered by ChatGPT)

There is no doubt that AI is an up and coming technology that continues to be improved and implemented into societal functions.  The reason for this is because of the positive impact AI has the potential to hold. At the start of this seminar, Professor Alexander spoke to the purpose of AI in society claiming that AI had the potential to 'make decisions' on our behalf  [1].  These decisions can have a tremendous impact on ourselves and our own lives, the things that we are exposed to and even the inspirations and values we hold. What is so important to note amongst the use of AI is the manner in which machine learning springs from the collective data the program is exposed to. When that data is indicative of note of racism and gender inequality, much of what AI is, becomes morally wrong and controversial.

In the article,  "Racist in the Machine: The Disturbing Implications of Algorithmic Bias" Megan Garcia shares a powerful quote from Laura Weidman Powers (founder of Code2040). This quotes follows as such:

We are running the risk of seeding self-teaching AI with the discriminatory undertones of our society in ways that will be hard to rein in because of the often self-reinforcing nature of machine learning. [2]

While much of this article speaks to the racial issues that persist in AI algorithms, Garcia also hints to the other underlying prejudices that exist within this technology. Referencing back How to Be Successful | A Collage, ChatBox AI is given the opportunity to be unbiased in its results as the inclusion of "person" in the submitted text is intended to make the results impartial to any specific identity. Yet, it is clearly evident that the machine favors the identity of a man. This shows the sort of unintentional prejudice that roots from societal norms. Women are often seen as lesser to men. To be of less value can also reflect the sort of success you posses. 

If we wish to improve as a society collectively and utilize and powerful technological system such as AI, we need to address the prejudices that come with machine learning. Gender discrimination has been a prevalent topic amongst history. Everything from healthcare to income falters to be impacted by the assumptions of gender. The World Health Organization spoke out to the use of AI noting, "human rights law and standards protect individuals against discrimination, promote inclusiveness, diversity and equity and safeguard 10 equality. Human rights relevant to AI also include privacy, data protection, freedom of expression, equality before the law and equitable access to essential services (including health care)" [3]. If we cannot reduce the prejudices that come with AI, then we are risking breaking the human rights every individual holds when they are in contact with AI. Beyond this, society collectively cannot move on to an ideal utopia - a space optimal for ingenuity and collective growth and prosperity. 

Posing the question of "beyond dystopia" is interesting. The process rendering multiple AI images with the caption "draw a successful person" resulted in highly emphasized gender implications. Yet, when asked directly how someone becomes successful, there is no indication whatsoever of gender being a factor in the pursuit of success. This is important to note. AI will oftentimes be flawed because collective society itself is flawed. To move beyond this dystopia is to simply  hold an awareness of the issues that persist with AI and its learning.  In the case of my experiment. I can dwell on the fact that AI is suggesting success only belongs to a man, but instead of doing this, I wish to move on from this flawed ideal and take away what is more important and relevant to me. This comes from the conversation I have with the machine. It is my choice to say I am capable of success even as a female; and in deciding that this is the only thing worthy of my time with AI, is to move away from the kind of controversy and dystopia this technology often embeds itself into.

1] Alexander, Amy J. "Vis 149 - Seminar in Contemporary Computer Topics." Syllabus, University of California San Diego, CA, 2024.

2[ Garcia, Megan. “Racist in the Machine: The Disturbing Implications of Algorithmic Bias.” World Policy Journal 33 (2016): 111–17.

3] World Health Organization. “Ethical Use of Artificial Intelligence: Principles, Guidelines, Frameworks and Human Rights Standards.” WHO Consultation Towards 

the Development of Guidance on Ethics and Governance of Artificial Intelligence for Health: Meeting Report Geneva, Switzerland, 2–4 

October 2019. World Health Organization, 2021. http://www.jstor.org/stable/resrep35680.8.