Lawsuit against Twitter (X)

August 14 2024 - X (formerly Twitter) Faces Lawsuit (Panettieri, 2024). The legal issue identified in my keynote article is European data protection laws. NOYB states that Twitter (X) has not properly protected the privacy of its users and failed to be transparent on how the data collected will be used. The lawsuit came across as focusing on how X uses its users data. Ireland’s Data Protection Commission put an order in place to prevent Twitter (X) from using the data of its users for further developments, training or refining its AI systems (Reuters, 2024). “On a post on the social media platform on Wednesday, the X Global Government Affairs account said the order sought by the regulator was "unwarranted, overboard and singles out X without any justification." (Reuters, 2024). NOYB's lawsuit is part of a broader effort to ensure that major tech companies adhere to stringent data protection standards. Given the strict requirements of GDPR and the significant penalties for non-compliance, the outcome of this lawsuit could have important implications for X and its operations in Europe, as well as for the tech industry as a whole.

Specific Event Reported In The Keynote Article

The main problem is that X is accused of not following the General Data Protection Regulation (GDPR), a comprehensive data protection regulation in the European Union, to the fullest extent possible. NOYB, the legal organization that is suing Twitter has mentioned that users were not properly advised how their data was going to be used and failed to protect their privacy. There are plenty of Artificial Intelligence (AI) subfields, the one in question is more of a Machine Learning type of model. This type of AI subfield looks for patterns from a large pool of user data. By gaining user information it can predict user behavior, preferences, and interests.

Legal Issue With The Use Of Machine Learning

Although AI such as Machine learning is beneficial in a vast array of ways, it also has its legal and ethical issues. Such as; Privacy violations, obtaining proper consent of collecting data, data security, bias and discrimination, and data ownership and control. It should be decided by the users on how their data is used. Ethics might be questioned in upholding user control if there are plenty of issues that arise over the same legal matters. There are laws in place that prevent discrimination and legal issues can come up if the AI system gives results that discriminate the intended parties. Furthermore, users also have the right to know how tech companies plan to use the collected data. If a company fails to give proper notice and receive consent from its user to collect data it can also face legal implications.

Examples Of The Issue In The Application Of ML

Some issues that can arise in some Machine Learning (ML) models include; data privacy issues, ethical concerns, and incorrect data quality. An example data privacy issues would be when a Machine Learning algorithm is used for health diagnostics and access to sensitive medical records is needed. A patience rights can be violated if their health records are accidentally exposed to an authorized person or organization. In regards to ethical concerns, ML can be wrongfully used to intrusively violate ones privacy rights and there can also be room for error in identifying certain demographic groups which would lead to further ethical and legal issues in the use of ML.

The Risk To Businesses Posed By The Issue

The risk to businesses posed by Machine Learning issues can be weighed by the benefits provided. It can also be reduced by having a more hands on approach and supervision of AI models. AI-generated content, whether text, images, or other forms, can inadvertently infringe upon existing intellectual property (IP) rights. This might include patent, copyright, or trademark infringement. (Grace, 2023). Even with employee training and human supervision over AI tools, ethical concerns may also linger as some employees might rely too heavily on AI tools and cause a copyright infringement due to their negligence.

Who Could Be Harmed

Businesses will need to establish their own guidelines, including ethical ones, to manage these new risks—as some companies, like Google and Microsoft, have already done (Babic, 2023). The ones that could be harmed include the users of AI if they rely too much on the AI tools without proper critical thinking to analyze the data and confirm it to be accurate. The typical civilian can also be harmed if AI is used to scan through job applications and certain key words favor males over female applicants. These are just a few examples of who would be harmed as people can be harmed by self driving cars, biased loan lending, and as far as financial loss from investments based off of AI data.

How The Issue Can Mitigated

I believe the best way to mitigate issues related to using Machine Learning tools is by both further developing the AI for improved accuracy and to also have human supervision to manage the data. “Engaging with legal experts who know your business is essential. They can help you navigate complex IP, data protection, and contractual matters. Training employees on AI ethics and compliance can also help ensure AI is used responsibly within your organization, minimizing legal risks” (Grace, 2023). Although there are some risks associated with using Machine Learning we should not stop the further use and development of AI. There are already legal and ethical risks involved from simply getting in ones car and driving to work, doing ones taxes, and even starting a new business. Hence, risks for issues in privacy violations, data security, discrimination should not hinder us to stop using AI, but should encourage us to continue the innovation and improve its functionality.

References

Panettieri, J. (2024, August 30). Generative AI Lawsuits Timeline: Legal Cases vs. OpenAI, Microsoft, Anthropic, Nvidia, Intel and More. Sustainable Tech Partner for Green IT Service Providers. https://sustainabletechpartner.com/topics/ai/generative-ai-lawsuit-timeline/ 

Reuters. (2024, August 13). X hit with Austrian data use complaint over AI training. https://www.reuters.com/technology/x-hit-with-austrian-data-use-complaint-over-ai-training-2024-08-12/ 

Reuters. (2024, August 9). X agrees to not use some EU user data to train AI chatbot. https://www.reuters.com/technology/artificial-intelligence/x-agrees-not-use-some-eu-user-data-train-ai-chatbot-2024-08-08/ 

 Grace, R.(2023, December 11). SO Legal. Navigating the legal risks of AI for your business.  https://www.solegal.co.uk/insights/navigating-legal-risks-ai-your-business 

Babic, B. (2023, November 13). When machine learning goes off the rails. Harvard Business Review. https://hbr.org/2021/01/when-machine-learning-goes-off-the-rails 

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