Just last month, we had a great opportunity to be part of a larger conversation around AI standards.

In particular, we responded to this request for information (RFI) from the United States National Institute of Standards and Technology (NIST) to create a plan for Federal engagement that supports reliable, robust and trustworthy AI technologies via a common technical standard.

At Neo4j, we strongly believe – and I personally believe – that artificial intelligence should be guided not only by robust technical standards, but robust ethical standards as well. A key overlapping principle in both of those areas is context.

Learn why Emil Eifrem believes context is essential for AI standards – both ethical and technical

Contextual information not only results in better performing AI systems, but also in a clearer ethical perspective for those creating and shaping it. For example, context helps us understand the factors and pathways of logic processing (and be able to explain them) so we can hold organizations accountable for AI decisions.

Context – in both data and in life – is derived from connections, and what’s better at natively storing, traversing and analyzing connections than graph technology? Nothing.

So in response to the NIST request, last month we submitted an open letter – co-written by myself and my brilliantly talented colleague Amy Hodler – on why graph data technology should be considered as part of a technical standard for AI solutions.

Here’s a copy of the introduction we sent – details on the rest of the RFI are below:


To whom it may concern,

Re: RFI: Developing a Federal AI Standards Engagement Plan
The case for graph technology as a foundation for AI

We are writing in response to the request for information from the National Institute of Standards and Technology (NIST) regarding creating a plan for Federal engagement in the development of technical standards and related tools in support of reliable, robust, and trustworthy systems that use Artificial Intelligence (AI) technologies: document 2019-08818.

The potential power of artificial intelligence is expansive and will be used in ways we cannot yet imagine. Despite, and perhaps because of this, we have a duty to guide its development and application in ways that facilitate innovation and fair competition, public trust and confidence, while incorporating the appropriate protections.

We are Emil Eifrem and Amy Hodler, the Chief Executive Officer and Analytics and AI Program Manager for Neo4j, Inc., a California-based company. We have been involved for years with data technologies that specifically deal with how people, processes, locations, and systems are connected and interrelated.

Neo4j helps people make sense of data through graph technologies which naturally store, compute, and analyze connections and pathways among data points. AI and machine learning systems are more effective, trustworthy, and robust when underpinned by contextual information provided by graph platforms. We can assist the Federal government in understanding the significant role that connected data plays in AI and learning systems.

Today, Neo4j leads the graph platform category in installations which include numerous commercial and Federal projects including the Department of Defense, the United States Intelligence Community, as well as state and local government agencies. The U.S. Army has deployed Neo4j for tracking equipment maintenance in their procurement process. MITRE Corp uses Neo4j for managing cybersecurity, and NASA consolidates and references its past research with a Neo4j powered knowledge graph.

The private sector has often been a leader in technical standards, but we also believe that public-private initiatives fuel innovation and assure transparency. We are major contributors to open source projects and support non-profit organizations including our work with NASA and the International Consortium of Investigative Journalists (ICIJ) on the Panama Papers, which 3 years on has resulted in more than $1.2 billion in tax fraud investigations.

Working with both highly as well as lightly regulated industries and governments, we’ve learned that complex data – and its use in AI – are a worldwide concern, which no single organization should regulate alone. We are offering our suggestions and support in your efforts to develop standards for AI technologies.

In summary, context must be incorporated into AI to ensure that we apply these technologies in ways that do not violate our societal and economic principles. AI standards that don’t explicitly include contextual information will result in subpar outcomes as solution providers leave out valuable, adjacent information. We have attached our recommendations for standards and tools to guide AI technologies such that they become truly reliable, robust, and trustworthy.

With our sincerest regards,

Emil Eifrem, Neo4j CEO & Co-Founder
Amy E. Hodler, Neo4j Analytics & AI Program Manager


In the following weeks, Amy will go into further detail (her series starts here) – drawing upon the full report we submitted to the NIST – on how and why graph technology is the superior choice to provide ethical and economic context to AI solutions.

Whether through an official standards body or through marketplace-wide agreement, I hope that one day all artificial intelligence systems benefit from the ethical, economic and technical benefits of connected data context.



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Ed Danzer

Your correct in stating context is critical to AI.

The difficulty I see is how to create, manage and share context. I attended my first Neo4j training in Seattle WA in 2015 along with a person that was interested in learning how to implement Neo4j for managing a product knowledge project I have worked on since 1997. Since then I have paid two more people to attend training and have not had anyone able to create a proof of concept UI so I can load the database and interact with it. In July I attended the Seattle Graph Days and spoke with Amy some about how I felt the UI to create and manage context was missing and that without this basic feature true success in sharing context will be limited.

I have been in contact with Tim Lewis and Matt Ministri with Neo4j about having consulting done to develop a UI for creating context and ways to interact with the context. In your work NIST please keep in mind that the context will need to be a worldwide standard that starts with a specific language as the primary starting point. In my opinion the American language need to be the standard language of communication for AI. The words and phrases used for AI should be a standard that has free access for portions of use and interactions. There should also be levels of access that are fee based to support the people required to administer the database and review the changes or additions to the knowledge base to verify honesty.
Here is a short list of things that will be difficult to manage when creating and interacting with data and its context for broad usage.
• How different people use the same word or phrase for different meanings.
• How different industries define their processes.
• How to set levels of interaction with the database.
• How to police the interaction with the database.
You are welcome to contact me if you would like.

Amy Hodler

Thank you, Ed, for your thoughtful comments. I remember our conversation and appreciate your tenacity with the UI project. I look forward to someday seeing what you develop for direct human interaction with graphs.

In regards to AI standards, I agree that there’s a lot of work to be done and many angles to consider. (There are probably things we have yet to even think of!) Graphs can help by adding context to AI so people can more appropriately guide and monitor these systems, for example, in tracking data lineage to watch for inappropriate data changes. Although graph technology is a powerful tool for better AI systems, we still need to consider the various bigger contexts – and that’s a big job.

I’m heartened by how much interest there is in being responsible about AI systems and I’d encourage you to keep up your level of involvement. We need people to keep looking at how they can contribute!

Thank you for your thoughts.