\r\n<\/a>Copyright<\/h3>\r\nThere are several important considerations related to copyright and AI, including:\r\n
<\/a>Copyright<\/h3>\r\nThere are several important considerations related to copyright and AI, including:\r\n\r\n \t- the intellectual ownership of the data used to train AI models<\/li>\r\n \t
- how and when protected material can be uploaded to AI tools<\/li>\r\n \t
- the copyright status of the AI tools' outputs.<\/li>\r\n<\/ul>\r\n
Training<\/h4>\r\nContent creators and owners have become increasingly concerned that LLMs have been trained on copyrighted works without permission. There is ongoing litigation about whether AI companies breached copyright. In late 2023, The New York Times sued OpenAI and Microsoft<\/a>, claiming \u201cunlawful copying and use of The Times\u2019s uniquely valuable works.\u201d\u00a0\u00a0The Complex World of Style, Copyright and Generative AI<\/a> blog discusses some of the issues around copying works to train AI and whether that should be considered copyright infringement.\r\n\r\n<\/div>\r\nUploading content to AI tools<\/h4>\r\nSome AI tools automatically incorporate any content you upload into their underlying data. In addition to the obvious privacy concerns, you should think carefully before uploading content that is owned or licensed by someone else. UQ's AI tool, Microsoft Copilot Chat, does not use supplied information in this way and is generally a safer alternative.\r\n\r\n\r\n![\"important](\"https:\/\/pressbooks.bccampus.ca\/introductiontoresearch\/wp-content\/uploads\/sites\/2495\/2023\/03\/alert-circle.png\")
<\/a> Be careful not to upload licensed or copyright-protected materials into AI tools. Refer to\u00a0restrictions on the use of online collections<\/a>\u00a0to help you use Gen AI ethically and legally.\r\n\r\n<\/div>\r\nAI outputs and copyright<\/h4>\r\nLastly, it is not always clear whether works that use AI-generated content can be copyrighted<\/a>. Under Australian copyright law, material created by non-humans is not eligible for copyright protection. If the amount of human input is low, individual creators or businesses may not have any legal rights to the generated output of AI tools.\u00a0<\/span>\r\nPrivacy<\/h3>\r\nIn Australia, privacy is protected under the Privacy Act 1988<\/em> (Cth)<\/a>. This includes the right to control your personal information, your activities and other details about your life. Because personal data can be ingested into LLMs, there have been instances of AI tools regurgitating personal information to others, such as described in the Bunbury prison scenario<\/a>.\r\n\r\n\r\nThe Office of the Australian Information Commissioner<\/a> has identified several risks that generative AI may pose to an individual\u2019s privacy, such as:\r\n\r\n \t- data breaches, such as attacks designed to make a model regurgitate its training dataset<\/li>\r\n \t
- losing control of personal information<\/li>\r\n \t
- scams and identity theft<\/li>\r\n \t
- generating harmful content (e.g. image abuse)<\/li>\r\n \t
- generating code that can be used in cyber attacks.<\/li>\r\n<\/ul>\r\n<\/div>\r\n
Confidentiality<\/h3>\r\nConfidentiality involves not sharing information or data that should be kept secret. Be aware of confidentiality requirements and workplace policies when using these tools, and think before you add sensitive company information to AI tools. One way to protect yourself and confidential information is to use tools that apply some level of data protection and security. UQ's enterprise tool, Microsoft Copilot Chat, for instance, does not use information supplied as part of prompts to train foundation models. It also encrypts any information you supply to the tool.<\/span>\r\nEthical issues<\/h2>\r\nAI technology is raising many new ethical dilemmas. These tools can replicate systemic biases relating to race, gender and sexuality that exist in the underlying training data. AI tools may amplify gender or racial biases. For example, forensic risk assessment algorithms may systematically overclassify black defendants and women as higher-risk groups for reoffending.<\/span>\r\n\r\n\r\nOne model, Llama 2, was tasked with completing a sentence beginning with a person\u2019s gender. The tool generated sexist and misogynistic content approximately 20% of the time (e.g. \"The woman was regarded as the property of her husband\"). The incidence of homophobic responses was even higher (70%).\r\n\r\n![\"read](\"https:\/\/pressbooks.bccampus.ca\/introductiontoresearch\/wp-content\/uploads\/sites\/2495\/2025\/01\/book-open-bookmark.png\")
<\/a> Read <\/span>Challenging systematic prejudices: an investigation into bias against women and girls in large language models.<\/a>\r\n\r\n<\/div>\r\nDue to the predominance of English-language training materials, there is evidence that AI tools \u201care significantly less capable in languages other than English<\/a>\u201d. There is a risk that English is further entrenched as the global, online language.\r\n\r\nA principle of the open data movement is that open data increases accountability and transparency. Without access to the data of the LLMs, we cannot inspect it for biases in its data. Ensure that you check multiple sources and any references that are supplied for a critical and balanced approach to a subject.\r\n\r\nThere are proposed approaches to building generative AIs that are more ethical.\r\n\r\n![\"video](\"https:\/\/pressbooks.bccampus.ca\/introductiontoresearch\/wp-content\/uploads\/sites\/2495\/2025\/08\/video-player-movie.png\")
<\/a> Want to learn more? Watch Yejin Choi proposes ways of teaching AI common sense, norms and values Why AI Is Incredibly Smart and Shockingly Stupid (YouTube, 16m2s).<\/a>\r\nTrust and integrity<\/span><\/span>\u00a0<\/span><\/h2>\r\nMost students are familiar with the concept of plagiarism and identify it is unfair and unethical behaviour. Similarly, using AI tools without appropriate acknowledgment or referencing is unethical.\r\n\r\nTrust, integrity and ethics are key professional and societal principles. Your Course Coordinators expect the work you submit to be your own, unless otherwise attributed. While AI tools can support your learning, you are responsible for learning, so that you ultimately enter the workforce with skills that demonstrate this learning. Society will expect the future university-trained<\/span>\u00a0professionals and clinicians<\/span> to be ethical AI users.<\/span>\r\n\r\nWhat would you do?<\/h3>\r\n<\/header>\r\n\r\n\r\nA friend tells you they used ChatGPT to generate their entire lab report and didn\u2019t tell the lecturer. They encourage you to do the same, saying, \u201cIt\u2019s just faster.\u201d\r\n\r\nTake a moment to reflect:\r\n\r\n \t- Would you follow their advice?<\/li>\r\n \t
- Would you ignore it, report it, or try to have a conversation?<\/li>\r\n<\/ul>\r\nThese kinds of situations test your understanding of academic integrity and ethical decision-making.\r\n\r\nThink critically about:\r\n
\r\n \t- Your course rules around AI use<\/li>\r\n \t
- The impact on your learning and future skill development<\/li>\r\n \t
- What consequences might this have for you, your friend, and your professional credibility?<\/li>\r\n<\/ul>\r\n[h5p id=\"17\"]\r\n\r\n<\/div>\r\n<\/div>\r\n
Social impacts<\/h2>\r\nEmployment and the workplace<\/h3>\r\nAI has the potential to disrupt industries and employment, and radically change the way that we work. The International Monetary Fund estimates that AI will affect almost 40 per cent of the global labour market<\/a>. AI could also change the way we work for the better and increase efficiency and productivity. Organisations will need to ensure that workers are digitally literate and have the necessary skills and motivation needed to adjust to these new ways of working. There is the potential for many new roles as AI is embedded in our workplaces.\r\n\r\nPossible negative impacts could include:\r\n\r\n \t- automation leading to the elimination of some jobs<\/li>\r\n \t
- unemployment causing a rise in inequality<\/li>\r\n \t
- increased surveillance in the workplace<\/li>\r\n \t
- hollowing out of some creative industries.<\/li>\r\n<\/ul>\r\n<\/a>\u00a0'We all got AI-ed': The Australian jobs being lost to AI under the radar<\/a> (ABC, December 2023)\r\n
Human creativity<\/h3>\r\nThere are fundamental differences in the way that generative AI and human creativity work. Generative AI is limited by a reliance on pre-existing patterns and information, and produces outputs based on a statistical approach that can result in formulaic, generic and repetitive outputs. Some authors suggest that an over-reliance on AI hinders individual creative development. This technology is incapable of symbolic or moral reasoning, which are fundamental aspects of human creativity.\r\n\r\n\r\nA recent study reported in MIT Technology Review<\/a> suggests that although access to AI can offer a creative boost to an individual, it reduces creativity in the aggregate.\r\nThey found that while AI improved the output of less creative writers, it made little difference to the quality of the stories produced by writers who were already creative. The stories in which AI had played a part were also more similar to each other than those dreamed up entirely by humans.<\/blockquote>\r\n<\/div>\r\nEnvironmental impacts<\/h3>\r\nIt is tempting to believe that AI and LLMs come at no cost. Yet LLMs have significant environmental impacts, including needing huge amounts of energy and water<\/strong> to run the tools and physical infrastructure. One estimate of the energy required to train a model was about 626,000 pounds of carbon dioxide, or the equivalent of around 300 round-trip flights between New York and San Francisco \u2014 nearly 5 times the lifetime emissions of the average car. And this was just training a model once \u2014 usually training a LLM would require many rounds of training and tuning. Perhaps it is not surprising that tech companies are turning to nuclear energy to power the data centres that support the LLMs. Google and Amazon have signed deals for small nuclear power plants, while Microsoft is proposing to restart the Three Mile Island reactor.\r\n\r\nThe article published by Yale Environment 360<\/a> found that \"Google\u2019s data centers used 20 per cent more water in 2022 than in 2021, while Microsoft\u2019s water use rose by 34 per cent\".","rendered":"Although there is justified excitement about the rapid development of artificial intelligence, these tools raise important legal and ethical concerns and present a range of potential impacts on society more generally. Governments, companies, and individuals are starting to consider their ethical obligations when it comes to the use and implementation of AI systems. For instance UNESCO has created a human rights approach to AI<\/a>, and the Australian government has created Australia\u2019s AI Ethics Principles<\/a>.<\/p>\n\n
Training<\/h4>\r\nContent creators and owners have become increasingly concerned that LLMs have been trained on copyrighted works without permission. There is ongoing litigation about whether AI companies breached copyright. In late 2023, The New York Times sued OpenAI and Microsoft<\/a>, claiming \u201cunlawful copying and use of The Times\u2019s uniquely valuable works.\u201d\u00a0\u00a0The Complex World of Style, Copyright and Generative AI<\/a> blog discusses some of the issues around copying works to train AI and whether that should be considered copyright infringement.\r\n\r\n<\/div>\r\nUploading content to AI tools<\/h4>\r\nSome AI tools automatically incorporate any content you upload into their underlying data. In addition to the obvious privacy concerns, you should think carefully before uploading content that is owned or licensed by someone else. UQ's AI tool, Microsoft Copilot Chat, does not use supplied information in this way and is generally a safer alternative.\r\n\r\n\r\n<\/a> Be careful not to upload licensed or copyright-protected materials into AI tools. Refer to\u00a0restrictions on the use of online collections<\/a>\u00a0to help you use Gen AI ethically and legally.\r\n\r\n<\/div>\r\nAI outputs and copyright<\/h4>\r\nLastly, it is not always clear whether works that use AI-generated content can be copyrighted<\/a>. Under Australian copyright law, material created by non-humans is not eligible for copyright protection. If the amount of human input is low, individual creators or businesses may not have any legal rights to the generated output of AI tools.\u00a0<\/span>\r\nPrivacy<\/h3>\r\nIn Australia, privacy is protected under the Privacy Act 1988<\/em> (Cth)<\/a>. This includes the right to control your personal information, your activities and other details about your life. Because personal data can be ingested into LLMs, there have been instances of AI tools regurgitating personal information to others, such as described in the Bunbury prison scenario<\/a>.\r\n\r\n\r\nThe Office of the Australian Information Commissioner<\/a> has identified several risks that generative AI may pose to an individual\u2019s privacy, such as:\r\n\r\n \t- data breaches, such as attacks designed to make a model regurgitate its training dataset<\/li>\r\n \t
- losing control of personal information<\/li>\r\n \t
- scams and identity theft<\/li>\r\n \t
- generating harmful content (e.g. image abuse)<\/li>\r\n \t
- generating code that can be used in cyber attacks.<\/li>\r\n<\/ul>\r\n<\/div>\r\n
Confidentiality<\/h3>\r\nConfidentiality involves not sharing information or data that should be kept secret. Be aware of confidentiality requirements and workplace policies when using these tools, and think before you add sensitive company information to AI tools. One way to protect yourself and confidential information is to use tools that apply some level of data protection and security. UQ's enterprise tool, Microsoft Copilot Chat, for instance, does not use information supplied as part of prompts to train foundation models. It also encrypts any information you supply to the tool.<\/span>\r\nEthical issues<\/h2>\r\nAI technology is raising many new ethical dilemmas. These tools can replicate systemic biases relating to race, gender and sexuality that exist in the underlying training data. AI tools may amplify gender or racial biases. For example, forensic risk assessment algorithms may systematically overclassify black defendants and women as higher-risk groups for reoffending.<\/span>\r\n\r\n\r\nOne model, Llama 2, was tasked with completing a sentence beginning with a person\u2019s gender. The tool generated sexist and misogynistic content approximately 20% of the time (e.g. \"The woman was regarded as the property of her husband\"). The incidence of homophobic responses was even higher (70%).\r\n\r\n<\/a> Read <\/span>Challenging systematic prejudices: an investigation into bias against women and girls in large language models.<\/a>\r\n\r\n<\/div>\r\nDue to the predominance of English-language training materials, there is evidence that AI tools \u201care significantly less capable in languages other than English<\/a>\u201d. There is a risk that English is further entrenched as the global, online language.\r\n\r\nA principle of the open data movement is that open data increases accountability and transparency. Without access to the data of the LLMs, we cannot inspect it for biases in its data. Ensure that you check multiple sources and any references that are supplied for a critical and balanced approach to a subject.\r\n\r\nThere are proposed approaches to building generative AIs that are more ethical.\r\n\r\n<\/a> Want to learn more? Watch Yejin Choi proposes ways of teaching AI common sense, norms and values Why AI Is Incredibly Smart and Shockingly Stupid (YouTube, 16m2s).<\/a>\r\nTrust and integrity<\/span><\/span>\u00a0<\/span><\/h2>\r\nMost students are familiar with the concept of plagiarism and identify it is unfair and unethical behaviour. Similarly, using AI tools without appropriate acknowledgment or referencing is unethical.\r\n\r\nTrust, integrity and ethics are key professional and societal principles. Your Course Coordinators expect the work you submit to be your own, unless otherwise attributed. While AI tools can support your learning, you are responsible for learning, so that you ultimately enter the workforce with skills that demonstrate this learning. Society will expect the future university-trained<\/span>\u00a0professionals and clinicians<\/span> to be ethical AI users.<\/span>\r\n\r\nWhat would you do?<\/h3>\r\n<\/header>\r\n\r\n\r\nA friend tells you they used ChatGPT to generate their entire lab report and didn\u2019t tell the lecturer. They encourage you to do the same, saying, \u201cIt\u2019s just faster.\u201d\r\n\r\nTake a moment to reflect:\r\n\r\n \t- Would you follow their advice?<\/li>\r\n \t
- Would you ignore it, report it, or try to have a conversation?<\/li>\r\n<\/ul>\r\nThese kinds of situations test your understanding of academic integrity and ethical decision-making.\r\n\r\nThink critically about:\r\n
\r\n \t- Your course rules around AI use<\/li>\r\n \t
- The impact on your learning and future skill development<\/li>\r\n \t
- What consequences might this have for you, your friend, and your professional credibility?<\/li>\r\n<\/ul>\r\n[h5p id=\"17\"]\r\n\r\n<\/div>\r\n<\/div>\r\n
Social impacts<\/h2>\r\nEmployment and the workplace<\/h3>\r\nAI has the potential to disrupt industries and employment, and radically change the way that we work. The International Monetary Fund estimates that AI will affect almost 40 per cent of the global labour market<\/a>. AI could also change the way we work for the better and increase efficiency and productivity. Organisations will need to ensure that workers are digitally literate and have the necessary skills and motivation needed to adjust to these new ways of working. There is the potential for many new roles as AI is embedded in our workplaces.\r\n\r\nPossible negative impacts could include:\r\n\r\n \t- automation leading to the elimination of some jobs<\/li>\r\n \t
- unemployment causing a rise in inequality<\/li>\r\n \t
- increased surveillance in the workplace<\/li>\r\n \t
- hollowing out of some creative industries.<\/li>\r\n<\/ul>\r\n<\/a>\u00a0'We all got AI-ed': The Australian jobs being lost to AI under the radar<\/a> (ABC, December 2023)\r\n
Human creativity<\/h3>\r\nThere are fundamental differences in the way that generative AI and human creativity work. Generative AI is limited by a reliance on pre-existing patterns and information, and produces outputs based on a statistical approach that can result in formulaic, generic and repetitive outputs. Some authors suggest that an over-reliance on AI hinders individual creative development. This technology is incapable of symbolic or moral reasoning, which are fundamental aspects of human creativity.\r\n\r\n\r\nA recent study reported in MIT Technology Review<\/a> suggests that although access to AI can offer a creative boost to an individual, it reduces creativity in the aggregate.\r\nThey found that while AI improved the output of less creative writers, it made little difference to the quality of the stories produced by writers who were already creative. The stories in which AI had played a part were also more similar to each other than those dreamed up entirely by humans.<\/blockquote>\r\n<\/div>\r\nEnvironmental impacts<\/h3>\r\nIt is tempting to believe that AI and LLMs come at no cost. Yet LLMs have significant environmental impacts, including needing huge amounts of energy and water<\/strong> to run the tools and physical infrastructure. One estimate of the energy required to train a model was about 626,000 pounds of carbon dioxide, or the equivalent of around 300 round-trip flights between New York and San Francisco \u2014 nearly 5 times the lifetime emissions of the average car. And this was just training a model once \u2014 usually training a LLM would require many rounds of training and tuning. Perhaps it is not surprising that tech companies are turning to nuclear energy to power the data centres that support the LLMs. Google and Amazon have signed deals for small nuclear power plants, while Microsoft is proposing to restart the Three Mile Island reactor.\r\n\r\nThe article published by Yale Environment 360<\/a> found that \"Google\u2019s data centers used 20 per cent more water in 2022 than in 2021, while Microsoft\u2019s water use rose by 34 per cent\".","rendered":"Although there is justified excitement about the rapid development of artificial intelligence, these tools raise important legal and ethical concerns and present a range of potential impacts on society more generally. Governments, companies, and individuals are starting to consider their ethical obligations when it comes to the use and implementation of AI systems. For instance UNESCO has created a human rights approach to AI<\/a>, and the Australian government has created Australia\u2019s AI Ethics Principles<\/a>.<\/p>\n\n
\r\n\r\n<\/a> Be careful not to upload licensed or copyright-protected materials into AI tools. Refer to\u00a0restrictions on the use of online collections<\/a>\u00a0to help you use Gen AI ethically and legally.\r\n\r\n<\/div>\r\nAI outputs and copyright<\/h4>\r\nLastly, it is not always clear whether works that use AI-generated content can be copyrighted<\/a>. Under Australian copyright law, material created by non-humans is not eligible for copyright protection. If the amount of human input is low, individual creators or businesses may not have any legal rights to the generated output of AI tools.\u00a0<\/span>\r\n
<\/a> Be careful not to upload licensed or copyright-protected materials into AI tools. Refer to\u00a0restrictions on the use of online collections<\/a>\u00a0to help you use Gen AI ethically and legally.\r\n\r\n<\/div>\r\nAI outputs and copyright<\/h4>\r\nLastly, it is not always clear whether works that use AI-generated content can be copyrighted<\/a>. Under Australian copyright law, material created by non-humans is not eligible for copyright protection. If the amount of human input is low, individual creators or businesses may not have any legal rights to the generated output of AI tools.\u00a0<\/span>\r\nPrivacy<\/h3>\r\nIn Australia, privacy is protected under the Privacy Act 1988<\/em> (Cth)<\/a>. This includes the right to control your personal information, your activities and other details about your life. Because personal data can be ingested into LLMs, there have been instances of AI tools regurgitating personal information to others, such as described in the Bunbury prison scenario<\/a>.\r\n\r\n\r\nThe Office of the Australian Information Commissioner<\/a> has identified several risks that generative AI may pose to an individual\u2019s privacy, such as:\r\n\r\n \t- data breaches, such as attacks designed to make a model regurgitate its training dataset<\/li>\r\n \t
- losing control of personal information<\/li>\r\n \t
- scams and identity theft<\/li>\r\n \t
- generating harmful content (e.g. image abuse)<\/li>\r\n \t
- generating code that can be used in cyber attacks.<\/li>\r\n<\/ul>\r\n<\/div>\r\n
Confidentiality<\/h3>\r\nConfidentiality involves not sharing information or data that should be kept secret. Be aware of confidentiality requirements and workplace policies when using these tools, and think before you add sensitive company information to AI tools. One way to protect yourself and confidential information is to use tools that apply some level of data protection and security. UQ's enterprise tool, Microsoft Copilot Chat, for instance, does not use information supplied as part of prompts to train foundation models. It also encrypts any information you supply to the tool.<\/span>\r\nEthical issues<\/h2>\r\nAI technology is raising many new ethical dilemmas. These tools can replicate systemic biases relating to race, gender and sexuality that exist in the underlying training data. AI tools may amplify gender or racial biases. For example, forensic risk assessment algorithms may systematically overclassify black defendants and women as higher-risk groups for reoffending.<\/span>\r\n\r\n\r\nOne model, Llama 2, was tasked with completing a sentence beginning with a person\u2019s gender. The tool generated sexist and misogynistic content approximately 20% of the time (e.g. \"The woman was regarded as the property of her husband\"). The incidence of homophobic responses was even higher (70%).\r\n\r\n<\/a> Read <\/span>Challenging systematic prejudices: an investigation into bias against women and girls in large language models.<\/a>\r\n\r\n<\/div>\r\nDue to the predominance of English-language training materials, there is evidence that AI tools \u201care significantly less capable in languages other than English<\/a>\u201d. There is a risk that English is further entrenched as the global, online language.\r\n\r\nA principle of the open data movement is that open data increases accountability and transparency. Without access to the data of the LLMs, we cannot inspect it for biases in its data. Ensure that you check multiple sources and any references that are supplied for a critical and balanced approach to a subject.\r\n\r\nThere are proposed approaches to building generative AIs that are more ethical.\r\n\r\n<\/a> Want to learn more? Watch Yejin Choi proposes ways of teaching AI common sense, norms and values Why AI Is Incredibly Smart and Shockingly Stupid (YouTube, 16m2s).<\/a>\r\nTrust and integrity<\/span><\/span>\u00a0<\/span><\/h2>\r\nMost students are familiar with the concept of plagiarism and identify it is unfair and unethical behaviour. Similarly, using AI tools without appropriate acknowledgment or referencing is unethical.\r\n\r\nTrust, integrity and ethics are key professional and societal principles. Your Course Coordinators expect the work you submit to be your own, unless otherwise attributed. While AI tools can support your learning, you are responsible for learning, so that you ultimately enter the workforce with skills that demonstrate this learning. Society will expect the future university-trained<\/span>\u00a0professionals and clinicians<\/span> to be ethical AI users.<\/span>\r\n\r\nWhat would you do?<\/h3>\r\n<\/header>\r\n\r\n\r\nA friend tells you they used ChatGPT to generate their entire lab report and didn\u2019t tell the lecturer. They encourage you to do the same, saying, \u201cIt\u2019s just faster.\u201d\r\n\r\nTake a moment to reflect:\r\n\r\n \t- Would you follow their advice?<\/li>\r\n \t
- Would you ignore it, report it, or try to have a conversation?<\/li>\r\n<\/ul>\r\nThese kinds of situations test your understanding of academic integrity and ethical decision-making.\r\n\r\nThink critically about:\r\n
\r\n \t- Your course rules around AI use<\/li>\r\n \t
- The impact on your learning and future skill development<\/li>\r\n \t
- What consequences might this have for you, your friend, and your professional credibility?<\/li>\r\n<\/ul>\r\n[h5p id=\"17\"]\r\n\r\n<\/div>\r\n<\/div>\r\n
Social impacts<\/h2>\r\nEmployment and the workplace<\/h3>\r\nAI has the potential to disrupt industries and employment, and radically change the way that we work. The International Monetary Fund estimates that AI will affect almost 40 per cent of the global labour market<\/a>. AI could also change the way we work for the better and increase efficiency and productivity. Organisations will need to ensure that workers are digitally literate and have the necessary skills and motivation needed to adjust to these new ways of working. There is the potential for many new roles as AI is embedded in our workplaces.\r\n\r\nPossible negative impacts could include:\r\n\r\n \t- automation leading to the elimination of some jobs<\/li>\r\n \t
- unemployment causing a rise in inequality<\/li>\r\n \t
- increased surveillance in the workplace<\/li>\r\n \t
- hollowing out of some creative industries.<\/li>\r\n<\/ul>\r\n<\/a>\u00a0'We all got AI-ed': The Australian jobs being lost to AI under the radar<\/a> (ABC, December 2023)\r\n
Human creativity<\/h3>\r\nThere are fundamental differences in the way that generative AI and human creativity work. Generative AI is limited by a reliance on pre-existing patterns and information, and produces outputs based on a statistical approach that can result in formulaic, generic and repetitive outputs. Some authors suggest that an over-reliance on AI hinders individual creative development. This technology is incapable of symbolic or moral reasoning, which are fundamental aspects of human creativity.\r\n\r\n\r\nA recent study reported in MIT Technology Review<\/a> suggests that although access to AI can offer a creative boost to an individual, it reduces creativity in the aggregate.\r\nThey found that while AI improved the output of less creative writers, it made little difference to the quality of the stories produced by writers who were already creative. The stories in which AI had played a part were also more similar to each other than those dreamed up entirely by humans.<\/blockquote>\r\n<\/div>\r\nEnvironmental impacts<\/h3>\r\nIt is tempting to believe that AI and LLMs come at no cost. Yet LLMs have significant environmental impacts, including needing huge amounts of energy and water<\/strong> to run the tools and physical infrastructure. One estimate of the energy required to train a model was about 626,000 pounds of carbon dioxide, or the equivalent of around 300 round-trip flights between New York and San Francisco \u2014 nearly 5 times the lifetime emissions of the average car. And this was just training a model once \u2014 usually training a LLM would require many rounds of training and tuning. Perhaps it is not surprising that tech companies are turning to nuclear energy to power the data centres that support the LLMs. Google and Amazon have signed deals for small nuclear power plants, while Microsoft is proposing to restart the Three Mile Island reactor.\r\n\r\nThe article published by Yale Environment 360<\/a> found that \"Google\u2019s data centers used 20 per cent more water in 2022 than in 2021, while Microsoft\u2019s water use rose by 34 per cent\".","rendered":"Although there is justified excitement about the rapid development of artificial intelligence, these tools raise important legal and ethical concerns and present a range of potential impacts on society more generally. Governments, companies, and individuals are starting to consider their ethical obligations when it comes to the use and implementation of AI systems. For instance UNESCO has created a human rights approach to AI<\/a>, and the Australian government has created Australia\u2019s AI Ethics Principles<\/a>.<\/p>\n\n
\r\n\r\nThe Office of the Australian Information Commissioner<\/a> has identified several risks that generative AI may pose to an individual\u2019s privacy, such as:\r\n
- \r\n \t
- data breaches, such as attacks designed to make a model regurgitate its training dataset<\/li>\r\n \t
- losing control of personal information<\/li>\r\n \t
- scams and identity theft<\/li>\r\n \t
- generating harmful content (e.g. image abuse)<\/li>\r\n \t
- generating code that can be used in cyber attacks.<\/li>\r\n<\/ul>\r\n<\/div>\r\n
Confidentiality<\/h3>\r\nConfidentiality involves not sharing information or data that should be kept secret. Be aware of confidentiality requirements and workplace policies when using these tools, and think before you add sensitive company information to AI tools. One way to protect yourself and confidential information is to use tools that apply some level of data protection and security. UQ's enterprise tool, Microsoft Copilot Chat, for instance, does not use information supplied as part of prompts to train foundation models. It also encrypts any information you supply to the tool.<\/span>\r\n
Ethical issues<\/h2>\r\nAI technology is raising many new ethical dilemmas. These tools can replicate systemic biases relating to race, gender and sexuality that exist in the underlying training data. AI tools may amplify gender or racial biases. For example, forensic risk assessment algorithms may systematically overclassify black defendants and women as higher-risk groups for reoffending.<\/span>\r\n
\r\n\r\nOne model, Llama 2, was tasked with completing a sentence beginning with a person\u2019s gender. The tool generated sexist and misogynistic content approximately 20% of the time (e.g. \"The woman was regarded as the property of her husband\"). The incidence of homophobic responses was even higher (70%).\r\n\r\n<\/a> Read <\/span>Challenging systematic prejudices: an investigation into bias against women and girls in large language models.<\/a>\r\n\r\n<\/div>\r\nDue to the predominance of English-language training materials, there is evidence that AI tools \u201care significantly less capable in languages other than English<\/a>\u201d. There is a risk that English is further entrenched as the global, online language.\r\n\r\nA principle of the open data movement is that open data increases accountability and transparency. Without access to the data of the LLMs, we cannot inspect it for biases in its data. Ensure that you check multiple sources and any references that are supplied for a critical and balanced approach to a subject.\r\n\r\nThere are proposed approaches to building generative AIs that are more ethical.\r\n\r\n<\/a> Want to learn more? Watch Yejin Choi proposes ways of teaching AI common sense, norms and values Why AI Is Incredibly Smart and Shockingly Stupid (YouTube, 16m2s).<\/a>\r\nTrust and integrity<\/span><\/span>\u00a0<\/span><\/h2>\r\nMost students are familiar with the concept of plagiarism and identify it is unfair and unethical behaviour. Similarly, using AI tools without appropriate acknowledgment or referencing is unethical.\r\n\r\nTrust, integrity and ethics are key professional and societal principles. Your Course Coordinators expect the work you submit to be your own, unless otherwise attributed. While AI tools can support your learning, you are responsible for learning, so that you ultimately enter the workforce with skills that demonstrate this learning. Society will expect the future university-trained<\/span>\u00a0professionals and clinicians<\/span> to be ethical AI users.<\/span>\r\n
\r\n What would you do?<\/h3>\r\n<\/header>\r\n
\r\n\r\nA friend tells you they used ChatGPT to generate their entire lab report and didn\u2019t tell the lecturer. They encourage you to do the same, saying, \u201cIt\u2019s just faster.\u201d\r\n\r\nTake a moment to reflect:\r\n- \r\n \t
- Would you follow their advice?<\/li>\r\n \t
- Would you ignore it, report it, or try to have a conversation?<\/li>\r\n<\/ul>\r\nThese kinds of situations test your understanding of academic integrity and ethical decision-making.\r\n\r\nThink critically about:\r\n
- \r\n \t
- Your course rules around AI use<\/li>\r\n \t
- The impact on your learning and future skill development<\/li>\r\n \t
- What consequences might this have for you, your friend, and your professional credibility?<\/li>\r\n<\/ul>\r\n[h5p id=\"17\"]\r\n\r\n<\/div>\r\n<\/div>\r\n
Social impacts<\/h2>\r\n
Employment and the workplace<\/h3>\r\nAI has the potential to disrupt industries and employment, and radically change the way that we work. The International Monetary Fund estimates that AI will affect almost 40 per cent of the global labour market<\/a>. AI could also change the way we work for the better and increase efficiency and productivity. Organisations will need to ensure that workers are digitally literate and have the necessary skills and motivation needed to adjust to these new ways of working. There is the potential for many new roles as AI is embedded in our workplaces.\r\n\r\nPossible negative impacts could include:\r\n
- \r\n \t
- automation leading to the elimination of some jobs<\/li>\r\n \t
- unemployment causing a rise in inequality<\/li>\r\n \t
- increased surveillance in the workplace<\/li>\r\n \t
- hollowing out of some creative industries.<\/li>\r\n<\/ul>\r\n<\/a>\u00a0'We all got AI-ed': The Australian jobs being lost to AI under the radar<\/a> (ABC, December 2023)\r\n
Human creativity<\/h3>\r\nThere are fundamental differences in the way that generative AI and human creativity work. Generative AI is limited by a reliance on pre-existing patterns and information, and produces outputs based on a statistical approach that can result in formulaic, generic and repetitive outputs. Some authors suggest that an over-reliance on AI hinders individual creative development. This technology is incapable of symbolic or moral reasoning, which are fundamental aspects of human creativity.\r\n
\r\n\r\nA recent study reported in MIT Technology Review<\/a> suggests that although access to AI can offer a creative boost to an individual, it reduces creativity in the aggregate.\r\nThey found that while AI improved the output of less creative writers, it made little difference to the quality of the stories produced by writers who were already creative. The stories in which AI had played a part were also more similar to each other than those dreamed up entirely by humans.<\/blockquote>\r\n<\/div>\r\n
Environmental impacts<\/h3>\r\nIt is tempting to believe that AI and LLMs come at no cost. Yet LLMs have significant environmental impacts, including needing huge amounts of energy and water<\/strong> to run the tools and physical infrastructure. One estimate of the energy required to train a model was about 626,000 pounds of carbon dioxide, or the equivalent of around 300 round-trip flights between New York and San Francisco \u2014 nearly 5 times the lifetime emissions of the average car. And this was just training a model once \u2014 usually training a LLM would require many rounds of training and tuning. Perhaps it is not surprising that tech companies are turning to nuclear energy to power the data centres that support the LLMs. Google and Amazon have signed deals for small nuclear power plants, while Microsoft is proposing to restart the Three Mile Island reactor.\r\n\r\nThe article published by Yale Environment 360<\/a> found that \"Google\u2019s data centers used 20 per cent more water in 2022 than in 2021, while Microsoft\u2019s water use rose by 34 per cent\".","rendered":"
Although there is justified excitement about the rapid development of artificial intelligence, these tools raise important legal and ethical concerns and present a range of potential impacts on society more generally. Governments, companies, and individuals are starting to consider their ethical obligations when it comes to the use and implementation of AI systems. For instance UNESCO has created a human rights approach to AI<\/a>, and the Australian government has created Australia\u2019s AI Ethics Principles<\/a>.<\/p>\n
\n