Artificial Intelligence Law Advisor

Management of intellectual property

• How can companies use trade secret, copyright, and other intellectual property regimes to protect the value of data sets and algorithms?
• How can the involvement of counsel in early-stage AI development help mitigate risk and protect proprietary work product?
• What steps can be taken to clarify ownership rights of content generated by AI (especially where different parties are involved in the creation and further development of the AI application)?
• How can companies avoid litigation with employees over who owns the rights to intellectual property created by AI?
• What license terms are appropriate to control access to, and use of, data sets?
• How will intellectual property terms governing data and artificial intelligence-based services interact with data privacy commitments and consumer protection laws?

Mitigating risk through contractual terms

• What B2B and consumer-facing terms can reduce exposure to liability?
• What model contractual terms will promote the transparent and ethical use of consumer data and compliance with legal requirements?
• What laws create the most significant risk for AI development, and how can the risks of regulatory uncertainty be mitigated?
• What due diligence is needed before procuring AI-based services or acquiring an AI-powered start-up?

Regulatory licensing and certification

• What are the federal and state licensing and certification requirements for particular AI applications, such as self-driving cars or the analysis of healthcare data (e.g., the practice of medicine or telemedicine requirements)?
• How should industry standards and international guidance be used in developing best practices and/or legal requirements?
• In which regulatory proceedings should creators and customers of AI-based services participate?
• When does AI trigger a legal alphabet soup, such as addressing obligations established by HIPAA, FTC, COPPA, and FDA?
• What advocacy before legislative bodies and regulators may be helpful to incentivize investment in AI development (e.g., exemptions from licensing requirements and immunity from potential tort liability)?
• What are the implications of government agencies using machine learning?

Privacy & data security

• How can companies maximize use of, and access to, user-generated data while complying with privacy protections?
• What safeguards and tools can be used to reduce risks associated with handling consumer information?
• What best practices will promote transparency and protect consumer’s rights concerning information about them?
• What terms can be incorporated into agreements, policies, procedures, and rules of the road to improve the security of databases that are used to support AI technology and the appropriate use of the data and the results of AI?
• How should gathering information from and about children be handled?
• How can AI organizations deal with information that goes global, including determining what laws apply?
  

Liability and litigation

• What best practices will reduce exposure to tort law and intellectual property law (e.g., defamation, copyright infringement, and rights of publicity) when chatbots and other AI applications are used to develop creative content?
• How can AI companies reduce liability due to those who rely on the AI output, such as reliance on medical advice given by a chat bot or predictions of the likelihood that a population or an individual would develop a particular disease or health condition?
• How can employers reduce exposure to discrimination laws when they use AI to select and terminate employees or otherwise detect rogue behavior?
• How can companies anticipate trade secrets/non-compete issues involving the development of AI?
• What product liability schemes should govern products that incorporate AI technologies?

Algorithms and bias

• What steps can financial institutions and other businesses take to minimize exposure to claims alleging discrimination by algorithms that power FinTech?
• How does data mining discriminate?
• What does it mean for an algorithm to be biased?
• Can AI be used as a tool to correct for bias?

DWT’s clients are a reflection of the diversity of businesses touched by AI. From Fortune 500 companies to nascent startups, we provide guidance to organizations across all industries including energy, transportation, technology, media, communications, advertising, financial services, healthcare, and retailers. Examples of our work include:

• Advising leading cloud services and communications company with the development and integration of AI-powered chat bots to deliver healthcare services.
• Representing leading smart-home services company in licensing and transactional matters arising from the company’s deployment of personal digital assistant in China.
• Advising healthcare provider on legal issues presented by physically implanted “smart” sensors.
• Advising a media client on intellectual property issues implicated by the use of AI to analyze data that is subject to copyright protection.
• Conducting risk assessments (including vulnerability to cyberattacks), HIPAA risk analyses, and privacy impact assessment for AI products used in cybersecurity, including through analysis of data sets (data design and presentation), inventory of data, etc. for various companies that are exploring potential AI applications.
• Assisting healthcare entities and vendors in navigating regulatory landmines, such as HIPAA, fraud and abuse, licensure, and scope of practice issues.

By leveraging data and cognitive science tools such as ML, deep learning, and neural networks, DWT's AI clients are deploying a new generation of technology at the forefront of another industrial revolution, to automate systems, enhance processes, and predict outcomes. Our clients run the gamut from global market leaders such as Microsoft to startups like DataRobot and PolySync.

Advising clients on the cutting edge of AI/ML applications, tools, and technology
DWT's AI team members provide strategic guidance to clients deploying AI/ML-enabled applications such as computer vision, natural language processing, predictive analytics, and robotics to deliver innovative new services. Our multidisciplinary team includes attorneys from a broad spectrum of practice groups, including technology transactions, privacy and security, IP, media, communications, labor/employment, litigation, public policy, and regulatory groups. Leveraging our diverse expertise, we work closely with clients to secure rights, mitigate risk, and navigate evolving legal frameworks.

Navigating legal hurdles and unpacking ethical considerations
Through our multidisciplinary approach, DWT's AI team provides clients with advice and counsel on the novel issues presented by AI/ML technology and systems, including the drafting and negotiation of agreements related to the creation, ownership, use, and licensing of data derived from the IoT, edge computing, and AI systems; regulatory considerations for deploying bots and virtual personal assistants; IP and policy challenges of deploying autonomous systems and predictive analytics; and legal and ethical risks arising from the deployment of facial recognition technology and other biometric-based applications.