BETWEEN HUMANS AND MACHINES
We believe that everyone who is impacted by an artificial intelligence (AI) solution recommendation deserves to be treated fairly and equally.
We were propelled into action by the stories of the disadvantaged, missed opportunities, and perpetuated biases.
The AI solutions are here to stay.
The accidental flaws need not be.
Inability to easily determine trustworthiness of an AI solution is a monumental problem impacting all levels of our society.
We have all already witnessed a large number of instances where non-trustworthy AI solutions have led to many unintended - and sometimes deadly - consequences, such as discrimination (race, age, gender) and spread of disinformation.
As AI gets deployed at large scale, these issues, if unchecked, will only get amplified, leading to lawsuits, regulatory fines, dissatisfied customers, reputation damage, and erosion of shareholder value.
Academics, policy makers, and governments across the globe are increasingly recognizing the importance of AI Trustworthiness. It is imperative for all organizations creating, using, investing in, or regulating AI solutions to adopt and enforce AI Trustworthiness principles without delay.
Source: IBM’s multidisciplinary, multidimensional approach to trustworthy AI
State of AI Trustworthiness by the Numbers
of executives view ethics as a source of competitive differentiation
of general public trusts companies to be responsible and ethical in their use of new technologies such as AI
of executives strongly agree that their organizations’ practices and actions on AI ethics match (or exceed) their stated principles and values
of AI Trustworthiness champions are non-technical executives
We help organizations advance their trust in AI solutions through a human-led, technology-enabled approach.
Our unique perspective is shaped by broad industry, consulting, and academic experience.
Our team and the Subject Matter Expert (SME) Community consist of:
experienced industry experts,
seasoned C-suite advisors,
data scientists, and
who are active and published researchers within their domains of expertise.
Our human-led technology-enabled approach successfully combines two decades of strategy, management and technology consulting experience focused on advancing trust between humans and machines, with over 15 years of academic research across relevant AI trustworthiness domains.
Our methodology and AI Trustworthiness framework are the result of an in-depth analysis of the most current and reliable AI trustworthiness sources across the Globe, further enhanced and approved by our SME Community members.
We enable organizations that create or seek to use trustworthy AI do so with confidence.
AI Solution Trustworthiness Assessment
An in depth solution assessment covering ethical and technical aspects of design, data, algorithms, models, processes, procedures, and ModelOps:
Assess AI solution's risk and organizational maturity
Proactively identify issues that lead to unintended consequences
Develop issue mitigation strategy
Obtain AI solution trustworthiness certification
AI Trustworthiness Strategy Design / Re-design
Strengthen your organization's AI strategy by incorporating AI trustworthiness principles and best practices
Fractional Chief AI Trustworthiness Officer
Assisting organizations in establishing and operationalizing a Chief AI Trustworthiness Officer role, leveraging TrustVector’s multidisciplinary community of AI Trustworthiness Subject Matter Experts across relevant domains:
Ensure accountability for AI-related decisions and actions
Infuse ethical AI practices throughout AI solution lifecycle
Protect against unintended consequences of misbehaving AI
Guided by our mission and leveraging our multidisciplinary human-led technology-enabled approach for determining AI trustworthiness, we help:
1. Gain and Maintain Customer's Trust
Prove to your customers, investors, and regulators that the AI solutions you are creating are trustworthy
2. Increase Market Differentiation
Increase your differentiation in the market by demonstrating commitment to trustworthy AI across your solutions
3. Increase Product Revenue
Speed up the sales cycle and increase your AI product revenue
4. Minimize Risk
Stay on top of AI regulations, and minimize unintended consequences and regulatory risk
AI Buyers & Users
1. Identify and Remedy Issues
Proactively identify and remedy AI trustworthiness issues with the AI solution you are purchasing and using
2. Increase Solution Adoption
Rapidly increase solution adoption through a repeatable AI trustworthiness early issue detection process during the entire AI solution lifecycle
3. Attain Faster ROI
Attain desired ROI faster through early and continuous AI trustworthiness verification, combined with robust AI / ML Ops and data governance processes
4. Minimize Risk
Minimize risks associated with unplanned outcomes when making critical decisions
1. Uncover AI Trustworthiness Flaws Early
Uncover hidden trustworthiness flaws with the AI solutions you are investing in
2. Lower Investment Portfolio Risk
Lower your investment risk by uncovering AI Trustworthiness flaws early and often during and after the funding rounds
3. Minimize Litigation Risk
Reduce risk of expensive litigation through a continuous AI Trustworthiness monitoring process
1. Enhance Current Capabilities
Enhance your capabilities to regulate products that rely on AI recommendations
2. Advance Approval Process
Advance reliability of your approval process for AI enabled products
3. Reduce Risk to Consumers
Reduce risk of unforeseen negative impacts for the AI solution users (consumers)
Meet our leaders
Co-founder & CEO
Aleksandar is a co-founder and CEO of TrustVector, a Chicago based professional services organization focused on verifying trustworthiness of artificial intelligence (AI) solutions. TrustVector team enables organizations that seek to create and use trustworthy AI solutions do so with confidence by providing independent third party AI solution trustworthiness verification, and/or AI trustworthiness strategy design/redesign. Leveraging their multidisciplinary human-led technology-enabled approach, TrustVector helps AI technology creators prove to their customers, investors, and regulators that the AI solutions they are creating are truly reliable, further differentiating themselves from the competition by demonstrating commitment to AI trustworthiness across their solutions, increasing their AI product revenue, and minimizing unintended consequences and regulatory risk.
Aleksandar is a senior executive advisor with over 20 years of leadership experience in the setup, expansion, and management of professional services organizations and teams to successfully develop and take to market technology based services and solutions across US, Canada and Europe for primarily Pharma and Life Science companies.
Co-founder & CSO
As a co-founder and Chief Scientific Officer (CSO), Sonja is responsible for evaluating and setting TrustVector's scientific priorities, envisioning and leading development of scientific capabilities, and building academic partnerships. Sonja is also an Associate Professor in the Department of Applied Mathematics, College of Computing, at Illinois Institute of Technology. She discovers, studies, and models structure in relational data we encounter in our daily lives. Sonja’s academic research portfolio spans theoretical and applied problems including development of statistical models for discrete relational data, such as social networks, and use of machine learning to predict and improve the behavior of algebraic computations. Sonja is passionate about social responsibility, inclusion, community engagement, and empowering others. She leads the Socially Responsible Modeling, Computation, and Design (SoReMo) initiative, empowering students to enact the positive societal change they are passionate about within Illinois Tech, Chicago, and beyond.
If you believe what we believe, let's talk!
222 W. Merchandise Mart Plaza, Suite 1212
Chicago, IL 60654
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