In the digital age, where information is abundant and attention spans are short, it takes a master wordsmith to capture the essence of a thought-provoking article. Dr. Sarah Elaine Eaton’s piece on the future of academic integrity and the impact of artificial intelligence on writing and plagiarism is just such a gem and can be found here. Inspired by her insightful observations and summative ideas, I take the liberty of offering my own reflections on the positives and negatives of AI enhancement, with some vivid anecdotes to bring these points to life. The responses are prompted from AI and enhanced by myself as reflected on Point 1 below.

1. Hybrid Human-AI Writing Will Become Normal

1. Positive attributes:

• Hybrid human-AI writing can lead to more efficient and effective writing.
• Collaboration between humans and AI can produce unique and innovative ideas.
• AI can assist in tasks that are difficult or impossible for humans to accomplish alone.
• Hybrid writing can allow for a more diverse range of voices and perspectives in writing.
• AI can help to improve the quality of writing.

Negative attributes:

• Dependence on AI for writing may lead to a decrease in critical thinking skills.
• The use of AI in writing may result in a lack of originality and creativity.
• AI may reinforce biases or stereotypes that already exist in society.
• The use of AI in writing may lead to a loss of jobs for humans.
• There is a risk of plagiarism or ethical concerns when using AI in writing.

2. Human Creativity is Enhanced

2. Positive attributes:

• AI can inspire humans and provide new ideas and perspectives.
• Humans can learn from AI and develop new skills.
• The use of AI can lead to more efficient and effective creative processes.
• Collaboration between humans and AI can lead to greater innovation.
• AI can help to identify patterns and trends that humans may not be able to see.

Negative attributes:

• Excessive reliance on AI to boost creativity may result in a decline in analytical and evaluative reasoning abilities.
• There is a risk that humans may become overly reliant on AI for ideas.
• AI-generated content may lack the emotional depth and nuance of human-generated content.
• AI-generated content may lack the cultural context and understanding that humans possess.
• The use of AI in creativity may lead to a loss of jobs for humans. The increasing use of AI in creative fields has raised concerns about the potential displacement of human workers. As AI algorithms become more sophisticated and capable of producing creative outputs, there is a risk that they may replace human workers in various creative industries, such as graphic design, music composition, and content creation.
  
  This displacement could have significant social and economic consequences, particularly for those workers whose jobs are most vulnerable to automation. While some argue that AI will simply create new jobs and industries, others worry that the shift away from human labor could lead to widespread unemployment and income inequality.
  
  However, it is important to note that the impact of AI on employment is not predetermined, and much will depend on how individuals, businesses, and governments choose to respond to these technological changes. Efforts to reskill workers for new roles in the AI economy, along with policies that promote worker protection and social safety nets, will be critical to ensuring that the benefits of AI are shared fairly and equitably.

3. Language Barriers Disappear

3. Positive attributes:

• Tools that help humans to understand different languages can lead to greater cultural exchange and understanding.
• People can communicate and collaborate more easily across language barriers.
• Language barriers can be broken down, leading to greater diversity and inclusivity.
• The use of AI to translate languages can help to preserve endangered languages.
• International communication and collaboration can be facilitated by language translation tools.

Negative attributes:

• Over-reliance on translation tools may lead to a decrease in language learning and proficiency.
• AI translation tools may not always accurately convey the nuances and meanings of different languages.
• The use of AI translation tools may reinforce linguistic and cultural biases.
• There is a risk that humans may become too reliant on AI for translation, leading to a loss of jobs for translators.
• There may be ethical concerns related to the use of AI in translation, such as the possibility of using AI for surveillance.

4. Humans can Relinquish Control, but not Responsibility

Positive attributes:

• The ability to relinquish control to AI tools can free up time and mental resources for humans to focus on other aspects of writing, such as developing creative ideas and refining their arguments.
• Emphasizing human responsibility in the age of AI writing can help ensure that AI tools are used ethically and responsibly.
• AI can assist humans in tasks that are time-consuming or difficult.
• The use of AI can lead to greater efficiency and productivity in writing.
• Humans can choose to use AI tools as a way to enhance their writing process.
• The use of AI can lead to more accurate and

Negative attributes:

• The potential for humans to relinquish too much control to AI tools could lead to a loss of originality and creativity in writing.
• Holding humans responsible for how AI tools are developed may not be feasible, as the development of AI is often controlled by large corporations or other entities with their own agendas.
  
  For example, in the development of autonomous weapons or facial recognition technology, the responsibility for how AI tools are developed may not be entirely held by humans. These technologies are often developed by large corporations or government entities with their own agendas and priorities, which may not align with ethical or moral considerations. In such cases, it may be difficult to hold individual humans responsible for the development of these AI tools, while having a need for greater regulation and oversight to ensure responsible and ethical development.
• As AI technology progresses at a rapid pace, human development of safety measures is currently not be able to keep up. This is leading to a gap between the development of AI technology and the establishment of ethical and safety standards, which may put individuals and society at risk.
  
  For example, AI algorithms may be trained on biased data, leading to discriminatory outcomes, or they may be programmed with unintended consequences, leading to unpredictable behaviors.
  
  One short example of this is in the development of autonomous vehicles. While AI technology has advanced to the point where autonomous vehicles are becoming a reality, human development of safety measures may not be fast enough to ensure their safe and ethical deployment. For example, there may be questions about liability in the event of an accident involving an autonomous vehicle, or concerns about how to ensure that autonomous vehicles make ethical decisions in complex situations. These issues may require ongoing research, development, and regulation, which may not be able to keep pace with the rapid development of AI technology.
• The rapid pace of AI technology development is driven in part by the competitive nature of companies and countries, who seek to gain a strategic advantage over their competitors by developing more advanced AI technologies. This “race to the top” is incentivizing the rapid deployment of AI technology without proper consideration for ethical or safety concerns, as companies and countries prioritize speed, efficiency, market share, and ultimately profits over safety and responsibility.
  
  One short example of this is in the development of military AI systems. Countries may prioritize the development of AI-enabled weapons systems to gain a strategic advantage over their competitors, without proper consideration for the ethical or safety implications of such systems. For example, autonomous weapons systems may be developed and deployed without proper testing or regulation, leading to unintended consequences or loss of life. The competitive nature of countries and their desire to “one-up” each other in the development of military technology may be outpacing the call for safety measures to be put in place, leading to potential risks and consequences for individuals and society as a whole.

5. Attribution Remains Important

Positive attributes:

• Proper attribution can help support academic integrity by ensuring that individuals receive credit for their original work.
• Citing and referencing sources can also help readers and researchers find and access additional information related to a particular topic.

Negative attributes:

• In some cases, overly strict or rigid citation requirements can discourage creativity and innovation in academic writing.
  
  For instance, in some academic disciplines, such as the humanities, scholars may be encouraged to take creative risks and push boundaries in their research and writing.
  
  However, if they are required to adhere to overly strict or rigid citation requirements, they may feel constrained in their ability to express themselves and communicate their ideas effectively. This can ultimately discourage creativity and innovation in academic writing, and stifle the development of new and original ideas.
• The emphasis on citation and referencing can also create additional work and stress for writers, particularly when dealing with complex sources or unfamiliar citation styles.

6. Historical Definitions of Plagiarism No Longer Apply

Positive attributes:

• The transcendence of historical definitions of plagiarism in the post-plagiarism age allows for greater flexibility in defining and addressing issues of academic integrity.
• Adapting policy definitions of plagiarism to fit the current technological landscape can help ensure that academic institutions are effectively combating plagiarism in all its forms.
• The transcending of historical definitions of plagiarism allows for a more nuanced understanding of what constitutes academic misconduct.

Negative attributes:

• The transcending of historical definitions of plagiarism can lead to confusion and ambiguity around what is and is not acceptable in academic writing.
• Adapting policy definitions of plagiarism to fit the current technological landscape may be difficult for institutions that are resistant to change or lack the resources to implement new policies.
• The transcending of historical definitions of plagiarism may make it harder to hold individuals accountable for academic misconduct, as there may be more gray areas in what is considered acceptable.

Interesting, tangential anecdotes:

In 2010, historian Doris Kearns Goodwin was accused of plagiarism in her book “The Bully Pulpit” after it was discovered that several passages closely resembled those from other sources. Goodwin acknowledged the errors and apologized, noting that she had relied too heavily on her research assistants to provide proper attribution for certain passages. The incident highlighted the importance of personal accountability and attention to detail in academic writing.

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Attribution has always been important in academia and beyond. One of the most famous cases of plagiarism in modern history is that of Melania Trump’s 2016 Republican National Convention speech, which bore striking similarities to a 2008 speech by Michelle Obama. The controversy sparked intense discussion about the importance of proper attribution and the consequences of failing to do so. The incident served as a reminder that even high-profile figures must follow the rules of academic integrity and respect the intellectual property of others.

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In 2016, an AI called “The Next Rembrandt” was created, which used algorithms to create a new painting in the style of the famous Dutch artist. The painting was created by analyzing and synthesizing data from Rembrandt’s existing works. While some critics argued that this was not true creativity, others saw it as a remarkable achievement in the field of AI.

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The controversy that arose in 2019 over the use of an AI-generated portrait in a Christie’s auction. The portrait, titled “Portrait of Edmond de Belamy,” was created by a Paris-based collective called Obvious using a GAN (Generative Adversarial Network) algorithm. The portrait ended up selling for $432,500, which was more than 40 times its estimated value.

The sale sparked a debate about the definition of art and the role of AI in creating it. Some argued that the portrait was not truly “art” because it was created by an algorithm, while others saw it as an innovative and exciting example of how AI can be used to push the boundaries of creativity. The incident highlighted the need to reconsider traditional definitions and categories in light of rapidly evolving technological advancements.

What are your thoughts on AI, the need for a shift in plagiarism, and the ubiquitous blend of AI and human writing?