Artificial Intelligence (AI) is one of the fastest-growing technologies in the world today, and it’s making big waves in the business landscape. AI is being used to improve business processes, automate repetitive tasks, and provide insights that were once impossible to obtain.
AI technologies can significantly improve business processes and outcomes, but it is important to carefully consider the legal issues associated with implementation. Web3 organizations should be transparent about their use of AI and take a proactive and responsible approach to incorporate AI into their business models, organizations can reap the benefits of this transformative technology while complying with legal and ethical guidelines.
The use of AI clouds the ownership status of the music, art, and literature it produces. AI algorithms can generate outputs that are highly complex and difficult to attribute to a specific author. Unlike human-created works, These works lack the human element of creativity, which makes it challenging to determine who should own the output. As a result, AI-generated works are often referred to as “machine works,” which raises the question of whether they should be treated the same way as human-created works.
In general, IP law recognizes the creator of a work as the owner until those ownership rights are transferred. However, in the case of AI-generated works, it may not be clear who the creator is. The person who prompted the AI to generate its output and the person who created the training dataset and wrote the algorithm may both be able to make strong claims. If ownership accrues to the organization that developed or trained the algorithm, what happens when multiple organizations collaborate on developing or training a chatbot? Ownership must be explicitly defined and agreed upon by all parties involved to avoid potential legal disputes. The output generated by AI algorithms can be highly valuable. AI-generated works, such as music, art, and literature, can be sold or licensed for commercial purposes or converted to NFTs and other collectibles, raising questions about the distribution of profits.
In any event, ownership may prove irrelevant. Currently in the US work product is considered copyrightable intellectual property only if it is the result of human creativity. The US Copyright Office, however, recently stated that it would consider applications for digital pictures, poetry, and other art brought to life through AI if the person seeking the copyright can prove their “own original mental conception” – their input, creativity, and effort – is instrumental and significant and transcend the machine’s output. Prompts, no matter how innovative or instructive, do not qualify.
Another IP concern for organizations using AI technology is the risk of infringing on the IP rights of others. AI algorithms often are trained on datasets that contain copyrighted works, which can lead to unintentional infringement of IP rights. Additionally, organizations may unknowingly use AI models that incorporate patented technologies or trade secrets, which can also lead to IP infringement.
Finally, organizations using AI technology may also face challenges related to the protection of their own IP rights. AI algorithms and models can be reverse-engineered, which may result in the loss of trade secrets and other confidential information and the misappropriation of the innovations by competitors or other third parties.
AI often generates unexpected or unintended outcomes and learns and improve over time. This often delivers outcomes superior to those humans can produce but it can also create unforeseen consequences. Outcomes that are difficult to predict or control present unique challenges for manufacturers in anticipating and addressing potential safety issues.
For example, an AI-powered autonomous vehicle may malfunction and cause an accident. Or an AI-powered medical device used to diagnose illnesses may produce incorrect diagnoses due to a flaw in the algorithm. If these scenarios lead to financial loss, injury, or death, the affected party would be entitled to damages. In such cases, however, it can be challenging to determine who is responsible for the accident – the manufacturer, the software developer who designed the AI algorithm, or the person or business operating it.
Privacy and Data Security
AI algorithms require vast amounts of data to train and improve their performance, meaning organizations must collect and process significant amounts of personal and sensitive data. However, organizations must ensure that the data they collect is accurate, relevant, and obtained with the necessary consent from individuals. Additionally, organizations must ensure that they have robust security measures in place to prevent unauthorized access to the data they collect and process.
Another significant concern is the risk of data breaches and unauthorized access to sensitive information. AI technology relies on the collection, storage, and processing of vast amounts of data, which can be a tempting target for hackers and other malicious actors. Organizations must ensure that they have robust security measures in place to protect against data breaches and other security threats. This can include implementing data encryption, access controls, and other security measures to prevent unauthorized access to sensitive data.
AI technology can reflect and amplify societal biases. For example, if an AI algorithm is trained on a dataset that contains biased data, such as gender or racial bias, it may perpetuate these biases when making decisions. For example, if an AI algorithm used to evaluate job candidates is trained on historical data that is biased against certain groups, the algorithm may perpetuate this bias in its evaluations, resulting in discriminatory outcomes. This can create liability issues for the organization using the AI algorithm and may result in legal action being taken against the organization.
In addition, the lack of transparency in some AI decision-making processes can make it difficult to identify and address discriminatory outcomes. To mitigate these concerns, organizations must take steps to ensure that their AI algorithms are trained on diverse and unbiased datasets and that they undergo rigorous testing and validation to ensure that they are free from prejudicial conceptions. Organizations must ensure that they comply with relevant anti-discrimination laws, such as the Americans with Disabilities Act and Title VII of the Civil Rights Act, which prohibits discrimination on the basis of race, gender, age, and other protected characteristics.
AI is becoming more prevalent in our daily lives and is an essential tool for businesses. However, it’s necessary to follow AI laws to regulate this technology properly. Gamma Law’s AI attorneys can help businesses and individuals develop AI technology according to regulations, preventing damage, scams, and legal issues. Our team is well-positioned to provide expert legal assistance in all aspects of AI development, from transactions to regulation, cybersecurity, and data privacy.
Gamma Law is a San Francisco-based Web3 firm supporting select clients in complex and cutting-edge business sectors. We provide our clients with the legal counsel and representation they need to succeed in dynamic business environments, push the boundaries of innovation, and achieve their business objectives, both in the U.S. and internationally. Contact us today to discuss your business needs.