AMBP-L™

AMBP-L™ Certification

Introducing the Artificial and Machine Bias Prevention – Leader (AMBP-L)™ Certification for Ethical Technology Development

A graphic of a circuit board with AMBP-L stamped on it

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Program Introduction

  • Algorithmic Bias


Certification System

  • Competencies
  • Exam Process
  • Eligibility


Exam Preparation

  • Course Objectives
  • Schedule


Fees and Policies

  • AMBP-L™ Fees
  • Policies
  • Recertification
Register Today!

AMBP-L™ Program Introduction


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 This method of design is outdated.


Artificial intelligence (AI), machine learning (ML), extended reality (XR), and deep learning are the future. In order to balance this perspective, the future also entails developing applications for different users, with varying behaviors, expectations, attitudes, and needs (BEANs). Smart learning design requires understanding the nuances between these diverse groups, as well as thinking through the inadvertent implications of algorithmic calculations, data processing, automated reasoning, and decision making on unique users. Design elements should also include accessibility.



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.


IDC proposes a proactive solution that is designed to prevent unfair outcomes: The Artificial and Machine Bias Prevention – Leader (AMBP-L)™ Certification.

What is Algorithmic 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.


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 in the Harvard Business Review, the Brookings Institute, Forbes, Fortune, Medium, Tech Crunch, AI Business, MIT Technology Review, McKinsey Reporting Insights, CNBC, the New York Times, and more.


Preventing, correcting, and/or removing algorithmic bias is not easy. Presently, most companies quietly retire a product that has algorithmic errors—in hopes the media does not find out. However, IDC 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.

About the AMBP-L™ Certification System


IDC’s Artificial & Machine Bias Prevention - Leader (AMBP-L)™ program enhances enterprise value by bridging the future of technology with concerns about fairness, transparency, justice, trust, and ethical standards.

The certification demonstrates that leaders are employing a holistic process to identify, prevent, correct, and/or remove bias from innovative technologies.

As more companies adapt new algorithmic methods, robots, and machines post-COVID, 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), Extended Reality (XR), 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 assumptions 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 AMBP-L™ certification is a distinct track. The content for the certification was developed through a unique partnership between diversity and AI technology experts, and features the competencies outlined below.

AMBP-L™ Competencies


  • Types of Bias, Triggers, and Stereotypes
  • The Business Case for Debiasing AI, XR, and ML Applications
  • Linguistic Bias and Language Processing
  • Design Flaws and Filter Biases
  • Solving for Fairness
  • Removing Biased Coding Elements and Data Sets
  • Analyzing Discriminatory Trends
  • Diverse Teaming Models for User Acceptance Testing – UAT
  • Processes for Resolving Ethical Dilemmas and Setting Team Standards
  • Measuring Anti-Bias Accuracy Levels

Certification Exam Process


The assessment process consists of two components, and all Candidates must pass both portions. Knowledge, skills, and abilities will be assessed through an exam and a simulation.

A high-stakes, 100-question knowledge exam.

A gamified simulation where users will be responsible for removing biased data/elements, determining where bias is manifesting itself, and/or evaluating whether biased codes have been removed.

Candidates have one year from the date of registration to pass both portions of the exam in the CourseNetworking Learning Management System (the CN).


The exam cut score is 80.0% for both components of the assessment. Candidates may take the computer-based, proctored test using an electronic device at home or work. The total test time is three (3) hours. Candidates who require an accommodation may request an extended time test.

Exam Eligibility

Founders, IT Executives, and Tech Professionals

3 years of experience in coding, programming, developing, UX design, QA testing, and/or serving as a start-up founder and/or IT executive

Procurement and Risk Management Officials

3 years of experience in procurement, supply chain, supplier diversity, strategic sourcing, buying, etc.; or legal, audit, compliance, risk management, etc.

C-Suite, DEIA, HR, and Other Leaders

3 years of experience as a C-suite executive, DEIA champion, HR business partner, or other leadership role associated with managing stakeholder experiences

Exam Preparation

AMBP-L™ Course Objectives


  1. Understand customer and global community concerns about diversity, inclusion, fairness, accessibility, accountability, transparency, and bias.
  2. Initiate team conversations about the impact of biased software and systems on marginalized or diverse communities around the world.
  3. Balance self-regulation with concerns about fairness and privacy.
  4. Expand opportunities to operate effectively in different global markets.
  5. Provide more value to customers with advanced insights about your product’s bias-prevention capabilities.
  6. Reduce inefficiencies that lead to waste, dissatisfied customers, and/or lost sales.
  7. Eliminate costs associated with quality issues or product recalls.

AMBP-L™ Course Schedule


IDC’s preparatory course and/or materials are NOT a requirement for eligibility of this examination or certification. 


If Candidates elect to participate in the prep course, it will consist of 14 hours of live instruction. The prep course will be offered twice in 2024. All live online sessions are recorded and available for review over the course of one year from the date of registration.


  • Spring 2024: June 4, 11, 18, 25 at 1:00 to 4:30 PM ET 
  • Fall 2024: October 1, 8, 15, 22 at 9:30 AM to 1:00 PM ET
Register Today!

AMBP-L™ Fees and Policies


The costs of biased algorithms can far exceed the investment in IDC’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.


Fees


Test fees and related materials are for a one-time sitting only. All study materials will be provided online only. Fees must be paid in full before Candidate(s) receive access to the exam and/or the CN system. All Candidates may participate in the Exam Review Sessions.

AMBP-L™ Complete Package

Includes 4-week Zoom prep course, online study guide, access to the CN, and exam.
$824

AMBP-L™ Prep Course Only

Includes 4-week Zoom prep course, online study guide, and access to the CN. Exam not included.
$575

AMBP-L™ Exam Only

Includes the exam (includes retest and exam change fees) and access to the CN.
$299

Retests

Candidates who fail either portion of the AMBP-L™ examination are eligible to retake the assessment. Candidates must wait 28 days (approximately 4 weeks) before retesting. Each Candidate can only take the examination a maximum of three (3) times in one calendar year. A candidate is eligible for two exam retests in one calendar year. The retest fee is $299 per sitting.


Exam Changes

If one (1) year transpires and the Candidate has not completed the exam process, the Candidate’s access to the CN Learning Management System will expire. Candidates may renew their access to the CN system for a $299 exam change fee. Once the exam only fee has been paid, the Candidate will have another year to complete the program.


Withdrawals and/or Refunds

There are no refunds for membership, the exam, retest, or recertification fees. Candidates who withdraw from the prep course within 14 days of their registration date may receive a refund, minus a $275 administrative fee. No refunds will be provided, for any reason, after 15 days have expired. Candidates may choose to reschedule or make a substitution in the same calendar year (January 1st through December 31st) without being charged a fee. If a substitution is made in a subsequent calendar year, the $299 exam change fee applies.

Recertification and Other Policies


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 40 continuing education units (CEUs) every two years.


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 IDC before the prep course or prior to scheduling the exam.


Nondiscrimination Policy

The Institute for Diversity Certification prohibits discrimination on the basis of age, gender, race, religion, national origin, disability, sexual orientation, or any other characteristic protected by law.

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