Meet Noah.

Noah Kenney is a multi-disciplinary expert and has over 7 years of experience as a web developer, digital marketer, and data scientist. He is the owner and lead developer of Digital 520, one of the leading specialty web and marketing agencies in the country. Noah is perhaps best known for his work in Artificial Intelligence. He is the host of the popular ‘Building the Future with AI’ podcast, and is also the lead developer behind an IOS application that uses vision recognition and the phone’s optical sensors to diagnose pneumonia (bacterial or viral) from chest x-rays. The application makes each diagnosis in under 1 second and does so with a >95% accuracy rate, significantly higher than an average radiologist.

Noah is the President and Research Lead at the Disruptive AI Lab, a global research and development lab focused on using AI for good, with specific emphasis on AI in healthcare. A significant portion of his work is related to R&D of artificial neural network that models human consciousness through cognitive mirroring. He is also the lead researcher at the Ethical AI Forum, a global think tank working to ensure the ethical development and deployment of AI technologies. The Ethical AI Forum is currently authoring the Global Artificial Intelligence Framework (GAIF), the world’s most comprehensive AI framework ever written, of which Noah is listed as the lead author. 

Noah is a sought after consultant on a range of topics including business management, data and privacy compliance, and cybersecurity. He is a 5 time published author and a guest writer/speaker on many websites, blogs, and podcasts. Noah is also frequently sought out for his work in live production, including ground and arial cinematography, directing, and live event/concert light programming and operation. 

Noah is an independent researcher and regularly publishes academic papers, which cover topics including computational science and mathematics, electrical engineering, artificial intelligence, neural network models, data privacy, and economic analysis. Noah’s formal education at the undergraduate level is in economics and pre-law, at one of the nation’s top universities, the Georgia Institute of Technology, and at the graduate level in engineering from the University of Colorado, Boulder. Noah is also on both the instructional and research team at the Georgia Institute of Technology, with work in data privacy, AI model development, and computational mathematics. He holds over a dozen industry certifications and awards. 


Latest Podcast Episode

In this episode of the Noah Kenney Podcast we go beyond the hype of AI to discuss its real world risks, limitations, and benefits. We answer questions about whether an AI can truly be conscious, the dangers of physical harm and polarization, and the limitations of further AI advancements. We also discuss potential positive uses of AI, including AI for transaction fraud monitoring.

Episode Title: AI Concerns, Limitations, and Consciousness


Latest Research

Policy Proposal for Improving SDG 4, SDG 8, and SDG 9

This policy proposal contains seven policies for secondary schools to increase college matriculation rates (quality education), increase workforce salaries, and improve industry, innovation, and infrastructure. Each policy aligns to one or more Sustainable Development Goals (SDGs) outlined by the United Nations.

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An Improved Neural Network Model Architecture

This research presents a new model for a neural network structure that is loosely based on the design of atoms and molecules, allowing for a circular flow of data. This has the benefit of allowing for pass-through nodes (increasing efficiency significantly) and allowing us to more accurately predict the binary state of a particular node in advance (0 or 1).

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A Brief Analysis of the Architecture, Limitations, and Impacts of ChatGPT

First, we begin with a description of the technical architecture of ChatGPT and how it differs from other large scale artificial intelligence language models. From there, we define the current use cases of ChatGPT, followed by an analysis of some of the current limitations of ChatGPT. In particular, we look at the inability of ChatGPT to be creative, issues of perpetuating biases, and possibility of identification. Finally, we look at some of the likely key impacts of ChatGPT, including copyright considerations and economic ramifications. As much as possible, this analysis is done from a non-technical standpoint, and seeks to show how AI is beginning to connect with daily life.

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Differentially Private Data and Data De- Identification

This paper analyzes both differential privacy and data de-identification. While differential privacy seeks to create differentially private data through the use of mathematics, data de-identification seeks to anonymize data in such a way that it cannot be re-identified at a later date. In addition, we analyze the challenges of both methods of approaching privacy, including the possibility of data re-identification and verification of privacy, before addressing possible methods of mitigating these challenges. Such methods include setting outer bounds of data, utilizing shared central databases with larger datasets, and grouping data into fewer data category buckets. The merits and benefits of both methods are discussed as well.

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An Analysis of Triangulation in Geometrically Noisy Environments using Mathematics

This paper uses mathematics to analyze the challenges of geometrically noisy environments on triangulation. Given widely accepted algorithmic triangulation methods, such as O (n ln n) or a simpler O (n3) method, we can mathematically prove that triangulation of any two dimensional polygonal region is possible, albeit impractical in some cases. Further, we consider the implications of environments in which a z-axis is present, as seen in cellular triangulation. In many of the cases where consideration of the z-axis is necessary, we recognize the absence of a fixed or known point of origin and consider methods of addressing this challenge.

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An Analysis of the Increasing Processing Power of Modern Microprocessors

Traditional computational power calculations rely on the assumption that additional processing power is best achieved by a quantitative increase in transistors, and particularly through a quantitative increase in the number of metal-oxide-semiconductor field-effect transistors (MOSFETs). However, advancements in microprocessor architecture could fundamentally alter the method in which additional processing power is achieved, thus rendering traditional computational power calculations meritless.

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Certifications (partial list)


If you’re looking to take your business or technolical innovation to the next level, Noah can help. His extensive industry knowledge and experience makes him a highly effective consultant and he regularly saves businesses hundreds of thousands of dollars in mistakes. 


Are you looking for an engaging, charismatic, and well spoken speaker for your next event? Noah is available to share his wealth of knowledge with your event attendees and will customize his keynote or presentation to fit your audience. Book Noah for your next event today.


Given his various publications and industry contributions, Noah often appears in the media, in addition to being featured on many websites, blogs, and podcasts. Noah is also available for exclusive interviews, podcast guest appearances, and other media opportunities.


Looking to get in touch with Noah? For questions about Noah’s research, interview requests, or media publications, please get in touch using his contact form. A member of Noah’s team will be in touch as soon as possible. To follow Noah’s latest work, you may join his newsletter.