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PODCAST

Certified - Responsible AI Audio Course

The **Responsible AI Audio Course** is a 50-episode learning series that explores how artificial intelligence can be designed, governed, and deployed responsibly. Each narrated episode breaks down complex technical, ethical, legal, and organizational issues into clear, accessible explanations built for audio-first learning—no visuals required. You’ll gain a deep understanding of fairness, transparency, safety, accountability, and governance frameworks, along with practical guidance on implementing

education courses

All Episodes

2:07

Trailer

Certified - Responsible AI Audio Course ·

2025/10/14

en

22:36

Episode 50 — Culture & Change Management

Certified - Responsible AI Audio Course ·

2025/09/15

Policies and technical safeguards succeed only when embedded within an organizational culture that values responsibility. This episode introduces culture as the shared norms and behaviors shaping AI use, and change management as the process of embedding new practices. Learners explore the importance of leadership commitment, employee training, and incentive structures for sustaining responsible AI adoption. Without cultural alignment, responsible AI risks becoming a box-ticking exercise

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23:05

Episode 49 — External Assurance & Audits

Certified - Responsible AI Audio Course ·

2025/09/15

External assurance and audits provide independent validation that AI systems meet ethical, legal, and operational standards. This episode explains how audits examine governance structures, data practices, model performance, and compliance with regulations. Learners explore the difference between assurance, which may be flexible and continuous, and certifications, which provide standardized recognition. Increasing regulatory mandates, particularly under the European Union AI Act, are

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23:00

Episode 48 — Procurement & Third Party Risk

Certified - Responsible AI Audio Course ·

2025/09/15

Most organizations rely on third-party AI systems and services, creating exposure to risks outside their direct control. This episode introduces procurement and vendor risk management as critical components of responsible AI. Learners explore risks such as biased vendor models, weak security practices, unclear licensing, and lack of transparency in black-box systems. The concept of shared responsibility is emphasized, with organizations remaining accountable for outcomes even when vendors

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23:05

Episode 47 — Standing Up an RAI Function

Certified - Responsible AI Audio Course ·

2025/09/15

A Responsible AI (RAI) function provides organizations with the structure to oversee and guide AI use. This episode explains how to establish an RAI office or committee with clear roles, charters, and mandates. Key responsibilities include drafting policies, conducting risk assessments, training employees, and reviewing high-risk projects. Learners are introduced to the value of cross-functional teams, where legal, compliance, technical, and ethics perspectives are integrated into one

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23:09

Episode 46 — Public Sector & Law Enforcement

Certified - Responsible AI Audio Course ·

2025/09/15

AI systems in the public sector and law enforcement operate under intense scrutiny because of their potential to affect entire populations and fundamental rights. This episode explains applications such as welfare eligibility assessments, predictive policing, and surveillance tools. Learners examine risks including bias in policing models, proportionality in surveillance, and accountability in automated decision-making. Human rights frameworks and democratic values are emphasized as

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24:17

Episode 45 — Education & EdTech

Certified - Responsible AI Audio Course ·

2025/09/15

AI tools are transforming education through adaptive learning platforms, tutoring systems, and automated grading. This episode introduces opportunities for personalization, increased accessibility, and efficiency for educators. It also highlights challenges around privacy, fairness, and academic integrity. Learners review obligations such as protecting student data under regulations like FERPA and ensuring fairness in assessments across diverse student populations.Examples illustrate

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23:56

Episode 44 — HR & Hiring

Certified - Responsible AI Audio Course ·

2025/09/15

Human resources and hiring processes increasingly use AI to manage recruitment, screening, and workforce analytics. This episode highlights benefits such as reduced recruiter workload, improved efficiency in handling large applicant pools, and predictive tools for employee retention. It also introduces risks, including bias in screening models, fairness in candidate assessments, and transparency obligations for automated decisions. Learners are reminded of employment and anti-discrimination

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24:45

Episode 43 — Finance & Insurance

Certified - Responsible AI Audio Course ·

2025/09/15

AI systems in finance and insurance carry significant opportunities and risks. This episode introduces applications such as credit scoring, fraud detection, underwriting, and claims processing. Learners explore ethical challenges around fairness in credit decisions, transparency for consumers, and accountability for financial harms. Regulatory frameworks such as equal credit opportunity laws and insurance oversight are emphasized as critical compliance drivers.Examples illustrate adoption

en

24:43

Episode 42 — Healthcare & Life Sciences

Certified - Responsible AI Audio Course ·

2025/09/15

Healthcare and life sciences present some of the most promising but also most sensitive applications of AI. This episode explores opportunities such as diagnostic imaging, predictive analytics for patient care, and AI-driven drug discovery. It also emphasizes the high stakes: inaccurate outputs can cause direct harm, and sensitive health data demands strong privacy protections. Learners review regulatory oversight, including FDA guidance in the United States and medical device rules in the

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25:40

Episode 41 — Environmental & Social Sustainability

Certified - Responsible AI Audio Course ·

2025/09/15

AI systems consume significant resources, from the energy needed to train large models to the materials required for specialized hardware. This episode introduces environmental sustainability as minimizing ecological impact and social sustainability as ensuring that AI contributes to community well-being and equity. Learners examine challenges such as carbon emissions from large-scale compute, water use in data centers, and social costs tied to job displacement or unequal access to AI

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27:48

Episode 40 — Choice Architecture & Dark Patterns

Certified - Responsible AI Audio Course ·

2025/09/15

Choice architecture refers to how options are presented to users, while dark patterns are manipulative designs that steer users toward decisions not in their best interest. This episode explains the difference between ethical nudges, which support informed decision-making, and dark patterns, which exploit cognitive biases or obscure options. Learners explore the ethical and regulatory dimensions of design choices that directly affect autonomy, fairness, and trust.Examples illustrate dark

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20:44

Episode 39 — Inclusive & Accessible AI

Certified - Responsible AI Audio Course ·

2025/09/15

Inclusivity and accessibility ensure AI systems serve all users equitably, regardless of background, language, or ability. This episode defines inclusivity as designing for cultural, linguistic, and demographic diversity, and accessibility as designing for people with disabilities in line with frameworks like the Web Content Accessibility Guidelines (WCAG). Learners examine risks when AI excludes marginalized groups or fails to accommodate users with visual, auditory, or cognitive

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21:59

Episode 38 — Provenance & Watermarking

Certified - Responsible AI Audio Course ·

2025/09/15

Provenance and watermarking are methods for tracking and identifying AI-generated content. Provenance refers to capturing the history of data or outputs, often through metadata, cryptographic signatures, or blockchain-based records. Watermarking embeds visible or invisible markers into outputs to signal origin and authenticity. This episode introduces both techniques as tools for accountability, transparency, and combating disinformation. Learners see how these methods strengthen trust in

en

21:07

Episode 37 — Copyright & Licensing in GenAI

Certified - Responsible AI Audio Course ·

2025/09/15

Generative AI raises complex intellectual property questions about both training data and outputs. This episode introduces copyright as legal protection for creators and licensing as the framework governing permissions. Learners explore disputes over whether copyrighted works can be used in training datasets, the concept of derivative works when outputs resemble source material, and uncertainty about whether AI-generated outputs can be copyrighted. Current differences between U.S. fair use

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21:38

Episode 36 — Incidents & Postmortems

Certified - Responsible AI Audio Course ·

2025/09/15

Even with strong safeguards, AI systems inevitably experience failures or incidents that create harm or expose vulnerabilities. This episode defines incidents as unplanned events where AI causes unexpected outcomes and postmortems as structured reviews that identify root causes and lessons learned. Learners explore why blameless postmortems, which focus on systemic issues rather than individual blame, are essential for building a culture of accountability and resilience. Regulatory

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21:02

Episode 35 — Monitoring & Drift

Certified - Responsible AI Audio Course ·

2025/09/15

Monitoring ensures AI systems continue to perform as intended after deployment, while drift refers to changes in data or environments that degrade accuracy and fairness. This episode introduces three forms of drift: data drift, where input distributions change; concept drift, where relationships between inputs and outputs shift; and label drift, where outcome distributions evolve. Learners explore why ongoing monitoring is essential for detecting these issues before they cause harm.Examples

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23:00

Episode 34 — Human in the Loop

Certified - Responsible AI Audio Course ·

2025/09/15

Human-in-the-loop describes oversight models where people remain actively involved in AI decision-making. This episode explains three main approaches: pre-decision oversight, where humans review outputs before they are finalized; post-decision oversight, where audits evaluate outcomes after deployment; and real-time oversight, where humans monitor and intervene during operation. Learners understand why meaningful human control is central to regulatory compliance, ethical responsibility, and

en

17:21

Episode 33 — Designing Evaluations

Certified - Responsible AI Audio Course ·

2025/09/15

Effective evaluation frameworks are essential to ensuring AI systems perform reliably and responsibly. This episode introduces task-grounded evaluations, which measure performance in domain-specific contexts, and benchmark evaluations, which provide comparability across models. Risk-based evaluations are highlighted as prioritizing tests in areas with the greatest potential for harm. Learners understand that evaluation is not one-time but iterative, requiring continuous reassessment

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23:19

Episode 32 — Hallucinations & Factuality

Certified - Responsible AI Audio Course ·

2025/09/15

Large language models frequently generate outputs that sound convincing but are factually incorrect, a phenomenon known as hallucination. This episode introduces hallucinations as systemic errors arising from statistical prediction rather than true reasoning. Factuality, in contrast, refers to the grounding of AI outputs in verifiable evidence. Learners explore why hallucinations matter for trust, compliance, and user safety, particularly in sensitive sectors such as healthcare, education,

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51 results

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