Bioinformatics is essential for the management of data in modern biology and medicine. By finding more secure solutions we will be creating greater opportunity and more efficiency in medical research. ~Audrey Bentley
Bioinformatics is essential for the management of data in modern biology and medicine. By finding more secure solutions we will be creating greater opportunity and more efficiency in medical research. ~Audrey Bentley
Thanks to tools like ChatGPT, Google Gemini, and Microsoft CoPilot, Artificial Intelligence has become a part of people’s day to day life. The launch of the R1 model from Chinese company DeepSeek in January of 2025 made people who typically don’t pay attention to Tech news, not only take notice, but become very interested albeit concerned. Most of the world is still trying to understand the ever evolving landscape that is Artificial Intelligence and what that means for their future. With the unknown comes fear. How do we mitigate the concerns we have about the future of AI? Law-makers at the state and federal level have been asking themselves the same question. And with the launch of DeepSeek-R1 it’s added a serious sense of urgency. Before we can get into how to comply with AI we first need to understand what AI is, understand broadly how it works, what risks are currently involved, where the laws are now, and where they are likely headed.
Artificial Intelligence has been around a lot longer than most people realize. It was founded as an academic discipline in 1956.
Machine Learning: A subset of Artificial Intelligence that uses algorithms to learn from data and improve over time.
Deep Learning: A subset of Machine Learning that uses neural networks to perform predictive analytics.
Natural Language Processing (NLP): A type of AI that allows computers to understand and generate human language.
Generative AI: a type of AI that can create new content like text, images, or videos based on user prompts.
Let’s start with the basics before we dig in. Artificial Intelligence at its core is a field of computer science that concentrates on creating machines that are capable of executing tasks that typically would require human intelligence. When I say human intelligence I am referring to cognitive functions such as: reasoning, learning, and decision making.
WHY: The main reason AI is often used is to increase productivity and cut costs.
HOW: In order for AI to do it’s job it must first “learn.” It learns by analyzing large sets of data and by doing so it is then able to identify relationships and patterns.
The way I usually explain how Artificial Intelligence works to someone not in tech, is that it’s essentially pattern recognition. After patterns are recognized, it can then start performing functions and tasks, based off these learned patterns.
Data Collection: AI systems gather data through sensors or from prepared data sources
Data Processing: AI systems process the data to identify patterns and understand the environment.
Learning: AI systems learn from other experiences and adapt their behavior based on the results of their actions
Decision Making: AI systems use their knowledge to make decisions and perform tasks.
“It comes with colossal opportunities, but also threats that are difficult to predict. Whoever becomes the leader in this sphere will become the ruler of the world.”
Some examples of how AI is used: Data Analysis, Language Translation, Medical Imaging, Voice Recognition Fraud Detection.
Rule-Based AI: Follows set of instructions, works best for straight forward tasks.
Context-Based AI: Pays attention to details and behavior. Examples- Alexa & Siri.
Narrow-Domain AI: Has very specific purpose. Examples- AlphaGo, DeepBlue by IBM, and spam filters.
Reasoning AI: Looks for patterns and makes logical reasons. Tries to be more like the human thought process. Huge datasets are needed.
Artificial General Intelligence (AGI): Able to learn, think, and understand.
Artificial Super Intelligence (ASI): Hypothetical future stage of AI, able to surpass human intelligence in all aspects.
Self-Aware AI: These systems would not only possess consciousness but the ability to perceive their own existence, actions, and surroundings.
Transcendent AI: Could create new forms of “collective consciousness” but for now just a concept.
Cosmic AI: In theory it would be so advanced it could colonize planets.
God-like AI: Very hypothetical. Basically would exhibit characteristics resembling a god.
In 2023 hundreds of AI experts and other notable figures (such as Sam Altman, Bill Gates, and Sam Harris as well as many more) signed a statement declaring “Mitigating the risk of extinction from AI should be a global priority alongside other societal scale risks such as pandemics and nuclear war.” An argument for the AI concerns often lies in the fact that if/when AI surpasses us in intelligence they will then become uncontrollable. The reason we (humans) have been able to dominate other animals for so long is because our brains have very distinctive capabilities that other animals do not have.
There’s so many “what ifs” when it comes to Artificial Intelligence right now, and with the unknown comes fear. With fear comes the need for regulation. Lawmakers at every level feel the same sense of urgency in regards to AI. As of right now there is no single extensive federal regulatory body with the primary dedication being AI in the United States. I predict this will change in the future, but for right now there are existing agencies and frameworks that are being leveraged to address some of the risks related to this technology. One of the frameworks is from The National Institute of Standards and Technology (NIST) within the Department of Commerce: AI Risk Management Framework (AI RMF).
On January 23, 2025 President Trump signed an executive order to remove barriers to American leadership in Artificial Intelligence…”This order revokes certain existing AI policies and directives that act as barriers to American AI innovation, clearing a path for the United States to act decisively to retain global leadership in artificial intelligence.”
On the federal level there are some agencies that are currently providing some sort of protection for AI: The Federal Trade Commission (FTC) typically for deceptive practices. The Equal Employment Opportunity Commission (EEOC) to help protect against bias in hiring, and the Consumer Financial Protection Bureau (CFPB) for financial protection.
We need to continuously keep up with monitoring our AI systems for bias.
We need to ensure that we are implementing proper data protection measures.
It is imperative that we remember to always incorporate human oversight into regulating our AI systems and remember that Artificial Intelligence can “hallucinate” which is what it’s called when it makes a mistake.
In using predictive analytics you can use current and historical compliance data to predict potential future challenges.
Within the necessary frameworks AI can map risks to controls.
Even though there’s definitely a lack of guidance on the federal level when it comes to regulations and laws in regards to Artificial Intelligence, the individual states have definitely been attempting to fill in the gaps. State legislation typically focuses on a wide range of concerns. Areas of focus: Protection and Privacy for the Consumer, in particular informing them of when and how AI is being used. Also an area that is addressed is the problem of AI generated deep fakes. The states also put special focus on areas of high risk such as: Education, Healthcare, Employment, and Government Agencies. This is by no means meant to be an exhaustive list of state laws, I’m just going to highlight some of them but for more I highly encourage you to go to US STATE-BY-STATE AI LEGISLATION but here’s some examples of current regulations that pertain to AI in different states…
California AB 2355: This bill was introduced in February of 2024 and is an amendment of the Political Reform Act of 1974, this requires that electoral advertisements using AI generated OR substantially altered content feature a disclosure that the material has been altered. This is enforced by the Fair Political Practices Commission.
New York Local Law 144: This law, which started to be enforced on July 5, 2023, was the first law in the U.S. which requires employers to conduct bias audits of AI-enabled tools used for employment decisions. This law imposes notice and reporting obligations.
Colorado AI Act: Enacted in May of 2024 this law is considered the first comprehensive AI Legislation in the U.S., imposing duties on developers and those who deploy high-risk AI systems to avoid algorithmic discrimination and requiring disclosures to consumers. You can see more about this act here.
California SB 942: AKA California AI Transparency Act. Requires covered providers of generative AI systems to create AI detection tools for identifying content created by their AI Systems.
New York, Texas, and Virginia have banned the use of DeepSeek, and Chinese owned generative AI application, on state owned devices and networks.
States like Maryland and Connecticut have mandated that state agencies perform impact assessments to ensure that AI systems in use are ethical, trustworthy, and beneficial.