By Doug Sanzone, Veterans Business Outreach Specialist
Photo Courtesy of VBOC of the Dakotas
About the VBOC
The Veterans Business Outreach Center (VBOC) program is designed to provide entrepreneurial development services such as business training, counseling, and resource partner referrals to transitioning service members, veterans, National Guard and Reserve members, and military spouses interested in starting or growing a small business. U.S. Small Business Administration (SBA) has 22 organizations participating in this cooperative agreement and serving as VBOCs.
Not a day goes by without some mention of artificial intelligence or AI. On one side are those who claim that AI will solve all our problems, leaving humanity with little to do other than maintain our technology. On the other side are those who think that AI will take over the world, creating a dystopian existence of humanity serving superior machines or even deciding to end humanity’s existence itself.
After spending more than 30 years in the technology field, witnessing its ever-forward evolution, I can unequivocally state the answer will lie somewhere in between those extreme points. AI has been and will be a larger part of our technological toolkit as time goes on. Let’s learn some more about AI so we can both embrace the new applications and understand artificial intelligence’s limitations.
It began in 1763 when Richard Price posthumously presented “An Essay Toward Solving a Problem in the Doctrine of Chances” by Thomas Bayes, an English Presbyterian minister, statistician, and philosopher. This essay laid much of the foundational groundwork that would evolve into Bayesian probability theory, which fundamentally altered our approach to uncertainty and predictive analysis.
Bayes’ theorem revolutionized statistical methods by providing a systematic approach to making decisions where both uncertainty and the integration of prior knowledge are important inputs. Bayes heralded a paradigm shift underscoring the significance of prior information in forecasting and the decision-making process. Bayesian statistics are at the core of modern conditional probability estimation approaches, including probabilistic machine learning, sequential estimation, risk assessment, mapping, and information theory. A theory more than 250 years old is one of the backbones of our current AI craze.
The strategic adoption of AI technologies mirrors the principles of Bayesian inference, where existing knowledge and historical data serve as guideposts for future decisions. This approach gains importance as businesses traverse the complexities of integrating AI products, needing to emphasize the continual refinement of strategies based on emerging data. Let’s look at AI as not merely a technology tool but as a strategic asset grounded in principled, data-informed decision-making.
AI’s Application
AI’s application already covers a diverse spectrum, reshaping industries in some of the following ways:
- Customer Service: AI-driven chatbots or virtual assistants can deliver service 24 hours a day, seven days a week, for almost all frequently asked questions.
- Personalized and Automated Marketing: AI algorithms can analyze customer data to better target email campaigns and other online advertisements or personalized recommendations.
- Virtual Assistants: AI-driven systems like Siri, Alexa, and Google Assistant can help small businesses manage their day-to-day activities, improving productivity.
- Automated Bookkeeping: Bookkeeping tasks such as invoicing can now be automated.
- Data Analysis and Predictive Analytics: Open-source, freemium, or paid AI frameworks and libraries can analyze data quickly and accurately. These insights can help you make more informed decisions across your whole business process, including inventory management, pricing, and identifying customer trends
Self-driving vehicles, new medicines derived from genomic analysis, and facial recognition are just a few of the new AI-driven technologies. The possibilities seem only to be limited legal challenges surrounding AI. The legal challenges surrounding AI span diverse domains.
Here are some of the legal considerations businesses must monitor to navigate the quickly evolving AI landscape:
- Intellectual Property and Copyright: Are the works generated by AI eligible for copyright protection and ownership? Was any of the data you used to create it copyrighted? Is there a legal difference between human and AI-generated works? These are all questions that need to be answered and could affect your business if you have integrated AI products.
- Data Privacy and Protection: AI relies on large datasets for its training and operation. Existing regulatory frameworks such as the General Data Protection Regulation (GDPR) in Europe mandate strict guidelines for data collection, protection, and storage. Violations of these regulations can lead to punitive fines. Businesses leveraging AI must ensure compliance with these regulations, particularly regarding the handling of any personal data and getting user consent.
- Liability and Accountability: As AI begins making more autonomous decisions, delineating where the liability lies in instances of malfunction or actual harm poses intricate legal dilemmas that have yet to be answered. Identifying culpability amidst a distributed decisionmaking framework entails establishing legal concepts for what entails negligence, fraud, and product liability. These concepts will take time and legal challenges to evolve.
- Bias Mitigation: Discriminatory outcomes from an AI model could contravene current civil rights and equality laws. How your AI behaves will expose your business to both legal and reputational risks. Regulatory bodies are focused on enforcing fairness, transparency, and non-discrimination in AI deployment. Make sure you understand the rules so your AI doesn’t violate them.
The adoption of any new technology or process brings along with it the need to develop different procedures for handling contracts and disputes. With time, new and different use cases will be created and put into implementation. These cases will lead to the creation of whole new areas of regulatory and legal structure for businesses to follow.
The need to define responsibilities will be necessary to resolve conflicts among interested parties. Since this is all new, the whole infrastructure needs to be developed. Not only will everyone be dealing with new technology but the rules of the game itself have changed.
Will the framework for the different types of artificial intelligence be a defining characteristic of the legal treatments these products will experience? AI already has applications in the creative fields of art, music, and composition, with it still needing to be discovered exactly how to treat such creations.
When implementing probabilistic models that combine multiple decision trees to train a system’s operation, such as a self-driving vehicle, where does the liability lie? How can it be proved whether the software, hardware, or user is at fault in an accident? These are examples of the possible legal issues that will need to be resolved before we can see a full-blown implementation of AI.
There is no doubt that AI and all the derivative software developed over the coming years will transform many of our current business practices. Exactly how things will change and the speed at which these changes will occur is impossible to predict. Though technology moves fast and can do new and useful tasks, the actual adoption of novel technology products is often more difficult than anticipated.
Integrating new processes into older legacy systems takes time and costs. Businesses will only decide to use these new technologies when they know that the time and effort to integrate them into their existing processes is worthwhile. Until there are policies and procedures for older businesses to follow, the adoption of AI will move relatively slowly. As with any new product or service, once a routine is established, the overall use and speed of adoption will increase.
The implementation of AI products will be much easier for new businesses than the old ones. This may lead to a real competitive advantage for new entries into varying marketplaces. Processes that once took multiple people or systems may now be put together in more efficient structures with the integration of AI products. Without the need to bolt AI to existing business processes but by beginning from scratch, where once the advantage went to the legacy business with legacy processes, the winner may now be the one who can implement the paradigm-shifting power of artificial intelligence most quickly and efficiently. The adoption of our current improved AI may lead to a small first mover creating the next great company.
It is impossible to predict how AI will affect the business world, but we know for sure it will.
VBOC of the Dakotas
701-738-4850
und.edu/dakotasvboc
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4200 James Ray Dr
Grand Forks, ND