Geoffrey Hinton, known as the "godfather of AI," announced his departure from Google on Monday amidst concerns over the potential risks to society of unchecked artificial intelligence (AI). Adastra’s Dr. John Yawney, an expert with over a decade of professional and academic experience in AI, is available to delve into greater detail about some of AI’s difficulties.

Pros

1. Operational efficiencies – Many businesses have had enormous successes in using AI to increase product quality to profitability through greater efficiencies. From improvements in warehouse safety, supply chain management and product quality indexes and more, AI has contributed vast improvements to many organizations. It is scaling rapidly due to the increased amount of data creation and processing power.
2. Enhanced Decision-Making – The ability to make better decisions through AI enhancements including operational choices, complex problem solving, strategic adjustments and performance assessments – all in real time. Model explainability can also allude to new relationships between decisions and decision support variables that may not be immediately evident.
3. Technical Advancements – Allows organizations to make informed decisions with multiple data points more quickly and unlocks potential to greater insights across various unstructured data sources and provides the facility to solve new currently unsolved problems. 

Cons

1. Governance - Another level of governance responsibility is required. Managing this undertaking now will undoubtedly result in fewer issues down the road. Ensuring we are using AI responsibly is an important aspect of managing AI effectiveness.
2. Social Responsibility – We need to consider the moral compass of what might be required in the future. If we are replacing human workforce with robotics, how are we re-training those individuals. What social safety net is required? AI must be designed so that it is adding enough jobs to the workforce to replace those that it will supplant. However, this will require ongoing resource training and evolution within the workforce.
3. Fear of the Unknown – It is human nature to fear what we don’t understand. What happens when autonomous cars are hacked? Or if my washing machine starts communicating with my fridge? There are many hypotheticals on what changes AI may bring forward and many yet to be discovered.

Furthermore, there is great deal of talent working with computational speeds not imagined even five years ago while the addition of quantum computing will undoubtedly move AI efficiencies even farther along.

The future remains undetermined and Dr. Yawney would be happy to speak to the next frontier of AI and its pros and cons in greater depth.

Dr. John Yawney, Chief Analytics Officer at Adastra, has executive oversight of the Data Science Practice, leads the development of the AI solutions portfolio, and holds Adjunct Professor status at McMaster University. The advancement of the Analytics Space at Adastra Canada and global offices rely on John’s expertise and his development of practical but theoretically sound solutions and AI service frameworks, for which he leverages his joint academic and industry focus. John received his Ph.D. in Applied Mathematics from the University of Waterloo and has extensive experience with building production AI/ML systems and performing numerical and statistical analyses. His research portfolio/focus includes numerical simulations of nonlinear systems, epidemiological modelling, applied AI applications, and smart systems.

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