AMBP-L™ Credentials

Demonstrate AI Bias Mastery with AMBP-L™ Credentials

Preventing AI Bias is Everyone's Responsibility

In previous generations, algorithmic workflows and automated decisions were made without considering user nuances, or the unfair outcomes that could dramatically impact different identity groups. This method of design is outdated. In fact, researchers identify more than 150 different types of bias, and these flaws can infinitely combine and/or intersect to produce unfair and distorted outputs, as well as result in labeling errors, data collection gaps, and skewed patterns.

Smart learning design requires understanding the nuances between diverse groups, as well as critically think through the inadvertent implications of algorithmic miscalculations, flawed data processing, automated reasoning failures, and unfair decision making on unique users. Bias can also include inaccessibility. The next generation of AI will deliver innovations that incorporate both big ideas and technology for social good. Currently, there is a social impetus to utilize AI for a higher purpose—one that is aligned not only with an organization’s values but its purported benefits to society over the long-term.

This means that sustainability, or enduring success, is inextricably tied to forward-thinking and proactive firms who have a bold vision for the future. Addressing issues such as bias is not a reactive solution for these firms, where a fix or patch is developed later. From a competitive perspective, fixes and patches waste valuable resources such as time and money. It also decreases the application’s value to society’s different users. Don't waste your social capital. HLTWai™ and IDC have partnered to offer a proactive solution that will help prevent unfair outcomes but you have to do the work as an: Artificial & Machine Bias Prevention – Leader.

What is AI Bias?

Algorithmic bias describes systematic and repeatable errors in a computing system that creates unfair outcomes or allows one group of users to experience privileges over others. For example, a qualified individual completes an online application but their resume is screened out because the system used a proxy to determine the age of the Candidate.

Preventing, correcting, and/or removing AI Bias is not easy. Presently, some companies are working to find solutions, while others are simply ignoring the potential impacts. However, we developed a solution that provides the necessary subject matter expertise and skill to help companies understand how bias can manifest, as well as what to do to prevent or remove it.

The Depth & Breadth of a Global Problem

In his 1976 book, Computer Power and Human Reason, Artificial Intelligence pioneer, Joseph Weizenbaum suggested that bias could arise both from the data used in a program, as well as from the way a program is coded. Since then, the problems with bias in algorithms and machine learning have been extensively documented.

Globally, the conversation has branched off into AI ethics, safety, and fairness, with millions of queries regarding skewed outputs across major search engines and AI platforms. The risk is that your users understand how the machine can embed social and ethical issues better than your team can collaborate on solutions. Don't wait until there's a lawsuit or PR disaster, prevent bias now.

About The AMBP-L™

Purpose

The Artificial & Machine Bias Prevention - Leader (AMBP-L)™ certification demonstrates that leaders are employing a holistic process to identify, prevent, correct, and/or remove bias from innovative technologies.

An Interactive Experience

Our learning process validates your experience. The AMBP-L™ utilizes an interactive and immersive format, which includes a 5-day prep course; access to the CN learning management system; online or in-person conference attendance with experts (fee is included in the certification cost); and virtual collaboration.

The Assessment Process

The assessment process consists of two components, and all Candidates must pass both portions.

A high-stakes, 100-question knowledge exam
A 2027 AI Inclusion & Ethics Conference report. The types of reports that are acceptable are: (a) Risk & safety report; (b) Technology forecast report; (c) Customer accessibility & experience report. Samples are located in the CN Learning Management System.

The Benefits of Credentials & Our Certification Policies

The AMBP-L™ certification is a distinct and rigorous track. The content for the certification was developed through a unique partnership between inclusion and AI technology experts. Some information will provide a refresh, but there will be many concepts with which you are not familiar. Take the time to explore how you can better serve different stakeholder groups, as well as provide more value in your current role.

As more companies adopt advanced technology, the AMBP-L™ program applies a systematic and repeatable process to remove bias that was programmed, and/or iterated itself, in an enterprising system. The AMBP-L™ program is also designed to make the process of purchasing Artificial Intelligence (AI) and Machine Learning (ML) more transparent to buyers, who have a social responsibility to understand whether a system is inherently flawed with unfair outcomes. Beyond assuming that a system will or will not potentially cause harm to diverse users, the AMBP-L™ applies a data-driven process to monitor, assess and evaluate bias infiltration on an ongoing basis.

The costs of biased algorithms can far exceed the investment in HLTWai's certification system. In addition to brand impacts and backlash, organizations risk losing customers, revenue, employees, and lawsuits. The benefits of the AMBP-L™ program are immense. For a small fee, the work of AI engineers and scientists can be in-demand, while organizations can ask the right questions before spending millions on technology that is unusable.

Course Completion Process & Timeline

A Candidate is a professional who has not completed the program. A Designee has achieved AMBP-L™ credentials. As a technical certificate, Candidates should expect to spend 3-5 months completing the program. Each Designee will receive a digital badge and a completion certificate. The certification process is complete upon taking the 100-question high-stakes assessment and submitting the conference report.

Recertification

Upon achieving AMBP-L™ credentials, Designees have two (2) years to recertify. The recertification fee is $75 USD and AMBP-L™ Designees must show at least 20 Continuing Education Units (CEUs) every two years. The CEUs can be in a variety of different areas demonstrating skill and leadership, including college courses, workshop presentations, books, boards/task forces, conferences, volunteering, etc. Designees can obtain credits from an assortment of organizations.

Accommodations Policy

If a Candidate requires an accommodation for any reason during the prep course or exam, please request the accommodation during the application process. All testing accommodations must be approved by HLTWai™ before the prep course or prior to scheduling the exam.

Nondiscrimination Policy

HLTWai™ prohibits discrimination on the basis of age, gender, race, religion, national origin, disability, sexual orientation or any other characteristic protected by law.

Refunds, Substitutions & Transfers

The registration fee must be paid in full before Candidates receive their completion certificate and digital badge. Satisfaction guaranteed. No refunds permitted for any reason. Substitutions are permitted. Candidates may also opt to transfer to another cohort or take the program the following year. Maximum period of two years allowed to complete the program.