Contributed by: Meaden & Moore.
Computing intelligence has come a long way for the mainstream user. In just the past decade, we have seen this technology grow from simple machine learning to artificial superintelligence.
In business, implementing new AI software can feel a bit overwhelming, especially when leaders lack technological expertise. However, businesses that fail to embrace AI and other machine learning software are foregoing a fantastic opportunity to boost their productivity and improve efficiencies in nearly all areas of their business.
What is artificial intelligence?
Artificial intelligence is, at its simplest definition, the intelligence of machines. Rather than relying on human intelligence, businesses that use AI are harnessing the power of machines to solve problems and make decisions.
AI isn’t just one type of technology. It represents a varied and wide range of capabilities. We like to classify AI into one of the following three categories:
1. Machine Learning
Artificial Narrow Intelligence (ANI)Machine learning is the simplest and weakest form of AI. Machine learning uses data and algorithms to perform tasks without being fed specific instructions. The software gathers information, generalizes that information, and predicts what action to take next. Over time, with help from human correction and more data, it learns how to perform those tasks more accurately.
Natural language processing systems (like Siri and Alexa) and computer vision (which is used in self-driving cars) are examples of machine learning.
2. Machine Intelligence
Artificial General Intelligence (AGI)Machine intelligence takes machine learning one step further by having the software rely on a biological neural network to solve problems and perform tasks. Although currently theoretical, AI that uses a biological neural network will operate much like the human brain. The system will learn continuously from unlabeled and uncategorized data, forming a complex network of neurons that tell the centralized “brain” where to direct its focus.
3. Machine Consciousness
Artificial Superintelligence (ASI), also known as Machine consciousness, is another theoretical version of AI. Machine consciousness occurs when a machine’s intelligence surpasses that of humans in all aspects.
In business, there are a nearly infinite number of ways you can use artificial intelligence to improve your business. One of the most common and easily accessible is generative AI.
What is generative AI?
Generative AI is software that generates text, images, audio, etc., using information from predetermined data sets. The software identifies patterns and structures within those data sets to build new and unique results.
ChatGPT is the most well-known example of generative AI. ChatGPT is a chatbot that responds to questions or prompts, mimicking human responses. Businesses have tried incorporating it into their operations after seeing how powerful ChatGPT can be. However, generative AI software has its faults, and businesses should be careful when using it.
Generative AI can make up false information:
In a cringe-worthy case from 2023, one lawyer’s expertise was called into question when he used ChatGPT to craft a motion that used case law that had been completely fabricated by ChatGPT.
Generative AI can be biased:
Depending on how you pose the question, ChatGPT can produce biased results. This could steer your team away from finding the best solution, or it could prevent you from seeing the problem from all angles.
Generative AI may violate intellectual property law:
Though ChatGPT argues that it is exempt from copyright law under the “fair use” rule, AI may generate outputs that infringe upon or even reproduce copyrighted images, text, or audio. In a recent lawsuit against Stable Diffusion and other AI software companies, Getty Images points out that the images generated by these companies aren’t unique enough, as evidenced by the fact that some of the AI-generated images include the Getty Images watermark.
Even though generative AI has its weaknesses, there are many valid business uses for it if you use it the right way.
How should you use generative AI in business?
Use AI as a starting point:
Your business should harness the power of AI but should always validate the results. AI can be a fantastic way to brainstorm ideas, create a first draft, or build a new model, but a human should always review the AI’s output before you put it to use.
Choose your AI model wisely:
In general, ChatGPT uses any and all information on the internet to craft its responses. With other models, like Microsoft Azure’s OpenAI, you can pre-select the data it uses. For example, if you want your model to generate marketing emails or product descriptions, you can tell your software to only use your company’s prior marketing emails and product descriptions when generating new outputs. This will ensure consistency in brand communications over time and will ensure you’re not copying another company’s content.
Choose a secure model:
Using a secure AI system requires managing access to your data, which you should do from multiple perspectives:
- Encrypt your data,
- Keep logs of all activity,
- Communicate expectations with your team about how to keep data secure,
- Employ physical security controls on workstations and at data centers.
Fortunately, when you use a more reputable model for generative AI, you’ll likely have better security controls already embedded in the product.
To Summarize…
If your organization doesn’t allow for the use of AI, it’s falling behind. AI is the future of business. Although we have some concerns about using AI, there are many ways you can use it safely. It may require some thoughtful changes on your part, but those changes shouldn’t deter you from exploring further.
The software that you currently use likely already has embedded AI capabilities, so we recommend you begin by reaching out to your software providers to learn more about those options. But before you employ any sort of AI solution, reach out to a third-party consultant you trust.
Related AGN Global Business Voice publications:
Evaluating AGN Member Digital Maturity
Unleashing the Power of ChatGPT
Contributed by:
Meaden & Moore
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