DataScience Show Podcast

Mirko Peters
  • 5.0 (2)
  • BUSINESS
  • UPDATED DAILY

Welcome to The DataScience Show, hosted by Mirko Peters — your daily source for everything data! Every weekday, Mirko delivers fresh insights into the exciting world of data science, artificial intelligence (AI), machine learning (ML), big data, and advanced analytics. Whether you’re new to the field or an experienced data professional, you’ll get expert interviews, real-world case studies, AI breakthroughs, tech trends, and practical career tips to keep you ahead of the curve. Mirko explores how data is reshaping industries like finance, healthcare, marketing, and technology, providing actionable knowledge you can use right away. Stay updated on the latest tools, methods, and career opportunities in the rapidly growing world of data science. If you’re passionate about data-driven innovation, AI-powered solutions, and unlocking the future of technology, The DataScience Show is your essential daily listen. Subscribe now and join Mirko Peters every weekday as he navigates the data revolution! Keywords: Daily Data Science Podcast, Machine Learning, Artificial Intelligence, Big Data, AI Trends, Data Analytics, Data Careers, Business Intelligence, Tech Podcast, Data Insights. datascience.show Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

  1. Litigation Readiness: An Executive Playbook for AI‑Related Lawsuits

    20H AGO

    Litigation Readiness: An Executive Playbook for AI‑Related Lawsuits

    AI systems can create novel paths to legal exposure—consumer harm, discrimination suits, contract disputes, or regulatory enforcement—that escalate quickly if executives lack a prepared legal and operational response. This episode opens with a concise anonymized vignette where a production recommendation engine produced a pricing error that led to class-action threats and weeks of board-level crisis. Mirko then delivers a compact, non-technical playbook for litigation readiness: early case assessment triggers, preserving privileged internal communications, tamper-evident evidence collection, coordinating counsel and insurers, vendor indemnity triage, settlement vs remediation decision gates, and a funding runway for rapid remediation or defense. Listeners leave with a prioritized 30–90 day checklist to build a legal war-room runbook, board-ready KPIs for exposure tracking, and concrete negotiation language to embed in procurement and insurance conversations. Practical, executive-grade actions so leaders convert potential lawsuits into managed, fundable decisions; subscribe to DataScience.Show to stay prepared. That’s the difference between models and value. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.

    9 min
  2. Stand Up an AI Ethics Board: A 30–90 Day C‑Suite Playbook

    1D AGO

    Stand Up an AI Ethics Board: A 30–90 Day C‑Suite Playbook

    Too many organizations create advisory ethics groups that are polite but powerless. This episode opens with a short anonymized mini‑case: a product team ignored advisory recommendations, an algorithmic harm surfaced publicly, and remediation cost the company time, trust, and budget. Mirko then delivers a compact, pragmatic 30–90 day C‑Suite playbook: drafting a charter that grants pause and escalation authority, choosing a balanced membership model, defining evidence standards and severity bands, mapping decisions into procurement and product gates, and structuring transparent, legally vetted disclosures. To break monologue fatigue, a brief 3‑minute micro‑interview with an external ethicist adds an independent perspective on credibility and external stakeholders. Listeners get an immediately actionable checklist and an offer to download the 30–90 Day Launch Sprint pack (charter template, intake form, escalation matrix, sample agenda) in the episode notes so leaders can move from intention to enforceable governance. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.

    9 min
  3. Ecosystem AI: An Executive Playbook for Shared Models, Data & Partnership Governance

    3D AGO

    Ecosystem AI: An Executive Playbook for Shared Models, Data & Partnership Governance

    Strategic partnerships—joint ventures, channel integrations, data co-ops, and platform alliances—are where AI scale often happens, but they also create ambiguous ownership, data-usage friction, and misaligned incentives. In this 20-minute executive monologue Mirko opens with a concise vignette where an ungoverned marketplace integration created a revenue dispute and compliance exposure. He then delivers a non-technical playbook: classify partnership archetypes and executive stakes, draft minimal data-sharing and IP primitives executives can require, choose commercial models (revenue share, value-based pricing, credits), and assign operational responsibilities for monitoring, incident response, and exit. Listeners get board-ready KPIs (shared-value realization, data provenance completeness, partner incident MTTR), a prioritized 30–90 day pilot to structure one high-value partner integration, and negotiation language to bring to legal and procurement. Practical, decision-oriented guidance so leaders capture ecosystem scale while keeping accountability clear. Subscribe to DataScience.Show for more executive playbooks. That’s the difference between models and value. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.

    12 min
  4. Independent Assurance: An Executive Playbook to Commission, Fund, and Act on Third‑Party AI Audits

    4D AGO

    Independent Assurance: An Executive Playbook to Commission, Fund, and Act on Third‑Party AI Audits

    Internal reviews are necessary but not sufficient: independent third‑party audits translate technical findings into credible, fundable actions for boards, auditors, and insurers. This 20‑minute decision-first monologue opens with a concise vignette where an internal check missed a vendor dependency that external auditors later flagged, producing weeks of costly remediation. Mirko then presents a non‑technical playbook: scoping audits (governance, data provenance, model behavior, security, procurement), choosing credible auditors and conflict‑of‑interest guards, defining minimum deliverables (reproducible tests, executive summary, severity bands), budgeting and procurement clauses to require audits, and converting results into prioritized remediation lanes, contract remedies, escrow triggers, and board‑ready scorecards. Listeners receive a prioritized 30–90 day pilot to commission an audit for one critical model, sample scope language for procurement, and actionable KPIs to demand from auditors. Practical, decision-focused steps so executives get independent assurance without drowning in implementation detail. Subscribe to DataScience.Show for more executive playbooks. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.

    10 min
  5. Insure the Unknown: An Executive Playbook for Transferring AI Risk with Insurance, Warranties & Bonds

    5D AGO

    Insure the Unknown: An Executive Playbook for Transferring AI Risk with Insurance, Warranties & Bonds

    Many C-level leaders treat AI risk as internal control; few know how to transfer residual risk to insurance or structure warranties. This 20-minute executive monologue opens with a concise vignette where an algorithmic pricing error triggered a multimillion-dollar claim and insurer rejection. Mirko then presents a non-technical, decision-first playbook for AI Risk Transfer: inventory transferable exposures, convert SLOs into parametric triggers underwritten by insurers, design insurance-backed warranties and escrowed remediation funds, set measurable underwriting signals (loss-velocity, concentration, audit trails), choose between traditional liability, parametric policies, captive insurance, and performance bonds, and negotiate claims-ready contracts and premium models. Listeners get board-ready KPIs (insured-exposure ratio, claim-latency, premium-as-percent-of-TCO), a 30–90 day pilot to scope one insured product line, and negotiation language for procurement, legal, and treasury. Practical, fundable steps so executives can convert uninsured tail risk into priced, transferable instruments. Visit datascience.show/ai-insurance to download the AI Risk Transfer checklist. That’s the difference between models and value. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.

    13 min
  6. Model Freshness: An Executive Playbook for Recalibration, Seasonality, and Model Aging

    FEB 23

    Model Freshness: An Executive Playbook for Recalibration, Seasonality, and Model Aging

    Models degrade for predictable reasons—seasonality, shifting customer behavior, pipeline changes, and calendar-driven promotions—but executives rarely fund sustained freshness practices until revenue drifts. In this 20‑minute monologue Mirko opens with a concise vignette where a forecasting model missed a seasonal peak and cost inventory millions, then lays out a non-technical, decision-first playbook: define board-ready freshness signals (performance decay curves, cohort slippage, feature drift rate), map business calendars and cadence dependencies (promotions, fiscal cycles, product launches) to recalibration policies, and create a financed 'retraining runway' with explicit budget buckets for routine recalibration, emergency retrains, and validation sampling. Listeners get a 30–90 day pilot to inventory top models, set trigger thresholds, run a controlled recalibration, and present a single-page funding request to finance. Practical governance language and procurement clauses are included so leaders convert model upkeep from an invisible technical cost into a funded strategic capability. Visit datascience.show/model-freshness to download the Freshness Checklist. That’s the difference between models and value. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.

    9 min
  7. Model Marketplace: An Executive Playbook to Catalog, Certify, and Monetize Reusable Models

    FEB 20

    Model Marketplace: An Executive Playbook to Catalog, Certify, and Monetize Reusable Models

    Enterprises waste time, money, and trust when every team rebuilds similar models or reuses uncertified artifacts. This 20‑minute executive monologue opens with a concise vignette where duplicated churn-detection models produced inconsistent customer outcomes and ballooning costs. Mirko then delivers a non-technical playbook for building an internal Model Marketplace: how to inventory candidate models, set certification gates (performance, lineage, data-provenance, SLOs), design internal pricing or showback, and create a lightweight catalog and governance board to approve reuse. The episode includes pragmatic artifacts executives can commission immediately—catalog taxonomy, certification checklist, contract snippets for internal SLAs, and a 30–90 day pilot to certify the top 10 reuse candidates. Listeners get board-ready KPIs (reuse rate, cost-saved-per-model, certification latency) and negotiation language to align product, platform, procurement, and legal. CTA: download the Model Marketplace Starter Kit at datascience.show/model-marketplace. That’s the difference between models and value. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.

    10 min
  8. The Label Economy: An Executive Playbook to Treat Labeling as a Strategic Asset

    FEB 19

    The Label Economy: An Executive Playbook to Treat Labeling as a Strategic Asset

    High-quality labels are the unsung input that determines whether models deliver predictable business outcomes—or unpredictable risk. This 20‑minute executive monologue opens with a concise vignette where poor labeling inflated a fraud model’s false positives and cost the business millions in churn. Mirko then delivers a non-technical, decision-first playbook: how to treat labeling as a product (ownership, SLAs, unit economics), practical sourcing options (in-house teams, managed vendors, verified crowd, synthetic augmentation), measurable label-quality SLIs and sampling protocols executives can read, procurement clauses to guarantee provenance and remediation, and a simple budgeting rubric to convert label needs into funded line items. Listeners receive board-ready KPIs (label accuracy variance, labeling velocity, parity vs baseline, detection-to-fix latency), and a prioritized 30–90 day checklist to inventory high-impact labeling lanes, run a quality audit, and secure funding. Practical artifacts and negotiation language so leaders stop losing model value to invisible label debt. CTA: download the Label Economy Playbook at datascience.show/label-economy. That’s the difference between models and value. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.

    9 min
See All (44)

Ratings & Reviews

5
out of 5
2 Ratings

About

Welcome to The DataScience Show, hosted by Mirko Peters — your daily source for everything data! Every weekday, Mirko delivers fresh insights into the exciting world of data science, artificial intelligence (AI), machine learning (ML), big data, and advanced analytics. Whether you’re new to the field or an experienced data professional, you’ll get expert interviews, real-world case studies, AI breakthroughs, tech trends, and practical career tips to keep you ahead of the curve. Mirko explores how data is reshaping industries like finance, healthcare, marketing, and technology, providing actionable knowledge you can use right away. Stay updated on the latest tools, methods, and career opportunities in the rapidly growing world of data science. If you’re passionate about data-driven innovation, AI-powered solutions, and unlocking the future of technology, The DataScience Show is your essential daily listen. Subscribe now and join Mirko Peters every weekday as he navigates the data revolution! Keywords: Daily Data Science Podcast, Machine Learning, Artificial Intelligence, Big Data, AI Trends, Data Analytics, Data Careers, Business Intelligence, Tech Podcast, Data Insights. datascience.show Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

Information

  • Creator
    Mirko Peters
  • Years Active
    2025 - 2026
  • Episodes
    44
  • Rating
    Clean
  • Copyright
    © Mirko Peters
  • Show Website
    DataScience Show Podcast