Effective Leadership in a World of Artificial Intelligence
By Doug Van Dyke, MBA, CSP and CEO of Leadership Simplified
If knowledge is power, a savvy leader must continually educate themself.
— Doug Van Dyke, CEO of Leadership Simplified
In this article, we examine a broader perspective of Artificial Intelligence (AI). Yes, yes there is a sample AI policy for your consideration later in this piece. We begin in a moment with a look at Neural Language Models (NLLMs), then we do a deep-dive on AI, and we end with a quick comment on Artificial General Intelligence (AGI). Clearly, this is our geekiest article ever.
Part I – NLLMs
NLLM stands for Neural Language Model, which is a type of statistical model that attempts to predict the likelihood of a sequence of words given a context. In other words, it estimates the probability of a word given its previous words in a sentence. One popular variant of the NLLM is the Generative Pre-trained Transformer model (think ChatGPT), which has achieved state-of-the-art results on a wide range of natural language processing tasks. NLLMs are one of many types of publicly and commercially available artificial intelligences.
Part II – AI
Artificial Intelligence refers to the development of computer systems that can perform tasks that typically require human intelligence, such as learning, reasoning, problem-solving, and decision-making. AI systems are designed to analyze data, recognize patterns, and make predictions or recommendations based on that analysis. AI can be divided into two main categories: narrow or weak AI and general or strong AI. Narrow or weak AI systems are designed to perform specific tasks, such as speech recognition or image classification. These systems are trained using large amounts of data and rely on algorithms to analyze that data and make decisions. On the other hand, general or strong AI refers to machines that can perform any intellectual task that a human can. More on this in Part III. AI is used in a wide range of applications, from virtual assistants and chatbots to self-driving cars and medical diagnosis. The development of AI has the potential to revolutionize many industries, but it also raises important ethical and social questions that must be addressed.
Part III – AGI
Artificial General Intelligence (AGI) is an advanced form of artificial intelligence (AI) that aims to create machines capable of performing a wide range of intellectual tasks that are typically associated with human beings. AGI is characterized by the ability to learn, reason, plan, understand natural language, and solve problems in a general and autonomous way. For many, AGI is where things get scary. The advance of AGI is what may very well bring forth a national debate about some type of AI regulation (such as what the FDA is to food).
For now, we will focus on the Part II (AI) segment of this newsletter. Without further ado, here is the good, the potentially bad, and some internal guidelines to consider regarding Artificial Intelligence.
The Pros & The Cons
Positives of using AI:
- Increased efficiency and productivity: AI systems can automate repetitive or tedious tasks, allowing humans to focus on more creative and strategic work. This can increase efficiency and productivity in many industries.
- Improved accuracy and precision: AI systems can analyze large amounts of data and make predictions or decisions with a high degree of accuracy and precision.
- Better decision-making: AI can help humans make better decisions by providing them with data-driven insights and recommendations.
- Personalization: AI can be used to personalize products and services for individual users based on their preferences and behaviors.
- Improved safety: AI can be used to detect and prevent accidents in industries such as transportation and manufacturing.
Negatives of using AI:
- Job displacement: AI can automate many jobs that were previously performed by humans, leading to job displacement and unemployment in some industries.
- Bias and discrimination: AI systems can perpetuate biases and discrimination if they are trained on biased data or if the algorithms themselves are biased.
- Lack of transparency: Some AI systems are complex and difficult to understand, which can make it challenging to identify errors or biases.
- Security risks: AI systems can be vulnerable to hacking and cyber-attacks, which can put sensitive data at risk.
- Dependence on technology: As we rely more on AI, there is a risk that we become overly dependent on technology and lose some of our ability to think and make decisions independently.
So now, on to a sample Artificial Intelligence policy. But first, a disclaimer.
NOTE: The Leadership Simplified team are NOT attorneys and you always want to consult your human resources and/or legal departments before putting company policies into place.
Generic Artificial Intelligence (AI) Policy
- Benefits & Risks: We should, at all times, ensure that AI is developed and deployed in a way that maximizes its benefits while minimizing its risks.
- Responsible AI Development: The development of AI systems should prioritize ethical considerations and respect for human rights. AI should be designed to enhance human welfare, and any negative consequences of AI should be identified and addressed. To ensure responsible AI development, our organization will adhere to best practices in AI ethics, such as the IEEE Global Initiative for Ethical Considerations in AI and Autonomous Systems.
- Transparency and Accountability: AI systems will be transparent and accountable, with clear documentation of how they make decisions and what data they use. Developers should make an effort to avoid biases and discrimination in their systems, and they should be held accountable for any negative outcomes resulting from the use of their systems.
- Data Privacy and Security: The use of personal data in AI systems should be governed by robust privacy and security policies. AI systems should be designed to protect personal data and ensure that it is used only for its intended purpose. Our organization will implement safeguards to prevent data breaches and ensure the security of our systems.
- Workforce and Employment: AI has the potential to create significant disruptions in the labor market. We will take steps to mitigate these disruptions and ensure that the benefits of AI are shared across our organization and the broader society. This may involve investing in education and training programs to prepare employees for the jobs of the future and supporting initiatives to promote social mobility.
- International Cooperation: The development and deployment of AI are global issues that require international cooperation. As prudent, our organization may work with other countries and international bodies to develop shared standards for the responsible use of AI, promote research collaboration, and support the development of AI in developing countries.
- Ethical Considerations: Ethical considerations such as fairness, accountability, and transparency should be prioritized in the development and deployment of AI systems. In order to ensure that AI is used for the benefit of humanity, it is important to recognize the potential negative consequences of AI, such as the amplification of existing biases, and work to mitigate them.
- Continuous Learning and Improvement: The development of AI will be an ongoing process of learning and improvement. Our organization will be open to feedback and willing to adapt our systems to address any issues that arise. Research into the ethical and social implications of AI is also supported and encouraged.
Bottom Line: Successful organizations are always looking for an edge. The ethical use of AI certainly will give savvy organizations a competitive advantage. AI will be best leveraged by taking a long view. Strategically ponder medium-term and long-term ramifications of AI implementation. Will your use of AI increase morale? If not, will its implementation be worth the short-term & long-term efficiencies, profits, etc.? Leaders and organizations that turn a blind eye to examining AI through the lens of impacting their own industry do so at their own peril. Luckily, most of you are savvy leaders that guide learning organizations. Educate yourself and your people. Guide them through this unfolding, foggy forest. Set guidelines, and provide a bold vision. Build guardrails, and execute.
Until next time, be well.
Doug Van Dyke is a leadership development expert, executive coach, strategic planner, and Certified Speaking Professional. Contact him at firstname.lastname@example.org, www.leadershipsimplified.com, 941-776-1121.
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