Scope of AI CoE:

The scope of the Maximus-Attain AI/ ML Center of Excellence includes the following matters: cultivating knowledge and skill AI Specialists knowledge sharing Building AI skills in Business and Sales specialists Educating leadership and client perception on capability offering, trustworthiness, and "the why for AI" within Attain Provide a unified knowledge base of AI concepts from a Maximus Attain perspective utilizing this knowledge to create business opportunity Providing AI community outreach and thought leadership to the broader AI community Providing AI technical offerings internally to Maximus Attain Provide a central hub for AI talent within Maximus Attain with a focus on recruitment and retention Serve as a guiding light in the space of emerging technologies including topics such as edge and quantum computing, robotics, virtual reality (VR), blockchain, w3 and 5G, etc.

Our Lead Guiding Principles:

Beneficial to the Public

has two clear benefits to the public: (1) knowledge acquisition for technological understanding and growth and (2) application use cases across a wide range of fields. We set forth to help bring technological awareness of AI concepts, methodology and best practices to the broad public, in an attempt to make sure everyone who wants to understand the technology they are using is capable of doing so. The faster the public can become adapted to AI concepts, the greater ability we have to create products to benefit all. Furthermore, in designing our AI applications we take into account the entire scope of socioeconomic factors that the application's existence could help or hinder, and move forward in implementing the solution that serves the greatest good.

Infuse Ethics into Every Design

To develop and engineer AI products and services that will take deliberate steps to "do no harm". This means accounting for and minimizing unintended bias and discrimination, both in the system and the data used to create the system. Ensuring AI capabilities fulfill their intended functions while possessing the ability to detect and avoid unintended consequences, and the ability to disengage or deactivate deployed systems that demonstrate unintended behavior. Although deep learning models are frequently called “black box models”, transparency, understanding, and explainability should always be goals, to the extent possible

Safe and Secure Data Applications

At Maximus|Attain we build safe and secure AI systems and drive development in accordance with best practices in AI safety. AI Safety is a collection of methodologies that our organization strives to follow to manage risks in machine learning systems, e.g. unintended and harmful behavior that may emerge from poor design of real-world AI systems. We subscribe to the following three practices to insure AI safety in our development model: Develop guidelines for AI Safety: These guidelines comprise of rules and regulations that can help engender trust among the developers, users and beneficiaries of artificial intelligence. These guidelines should govern the ethical management of AI system’s operations as well as the conduct of its employees. Manage Integrity of Data: Organizations should implement techniques and processes to protect, detect, correct and mitigate risks due to anomalies. These techniques must be integrated end-to-end within the AI platform. Managing data integrity and implementing risk mitigation techniques are essential in AI systems. Validate and verify: For achieving robustness and safety, all AI systems should be verified, validated and tested, both probabilistically and logically before they are deployed. AI systems are tested in constrained environments and their operation needs to be continuously monitored after deployment. If AI systems are safely implemented, Organizations can gain valuable insights and can make more informed business decisions.

Robust System Design

We view AI Products as AI software, and not just models. We approach them in an agile and iterative fashion, deploying quickly to get end-to-end feedback on our code changes. Our AI System design incorporates Monitoring, Testing, Versioning, Data Management, and Explainability into the equation.

Accountable to end user

To develop and engineer AI products and services that not only serve to solve complex problems but are also guided and molded by those who use and rely on them. Users will be able to voice their feedback and concerns about any of our AI products and services which will be used to shape their continual development and improvement. In addition, our AI products and services are designed and developed with privacy at every stage to ensure data is secured, made available to appropriate users in order to give them control over the use of their own data.

Uphold Standards of Scientific Integrity

In the process of developing AI applications, we will use peer-reviewed materials and scientific literature that include verifiable evidence to maintain scientific integrity to the greatest extent possible. We are committed to developing AI applications with intellectual rigor, so our tools produce predictable, reliable, and trustworthy results. We will follow an objective pursuit of sourcing data for training AI systems that maintain a high standard of quality, transparency, and compliance to achieve their intended goals. We will work with a wide range of stakeholders to safeguard our AI capabilities against suppression or adulteration for political gain or in response to external pressures. We will provide thoughtful leadership in this area so that we may responsibly disseminate accurate knowledge about our AI applications as we work to expand our AI capabilities at Maximus | Attain.

Design for Compliance

As the scope and need for AI expands, so does the risk involved with model, legal, regulatory and operational compliance and the necessity to balance protecting citizens from potential analytical blunders with the necessity of keeping pace with the demand for increased predictive capabilities. As an organization we have tunnel vision towards maintaining compliance with our clients across all sectors and agencies by utilizing our breadth and depth of knowledge in incorporating agile, cloud, and DevSecOps best practices into our AI development along with proper data and project management.

Communicating ML Concepts in Business Language

We strive to communicate complex and abstract AI/ML concepts in terms, visuals, and other methods aimed at generating excitement and investment from business. It's not enough to be right, the decision-makers still have to want to do it too.

Main Goals

We must achieve these to be thought leaders of AI, ML ,DS, and RPA within Maximus Attain: Selling AI to clients in an alluring yet realistic manner blog posts creative writing based around AI