『DataScience Show Podcast』のカバーアート

DataScience Show Podcast

DataScience Show Podcast

著者： Mirko Peters
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概要

 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.

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Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.Mirko Peters 経済学
エピソード
  • Ecosystem AI: An Executive Playbook for Shared Models, Data & Partnership Governance

    Ecosystem AI: An Executive Playbook for Shared Models, Data & Partnership Governance
    2026/03/02
    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.
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    12 分
  • Independent Assurance: An Executive Playbook to Commission, Fund, and Act on Third‑Party AI Audits

    Independent Assurance: An Executive Playbook to Commission, Fund, and Act on Third‑Party AI Audits
    2026/03/01
    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.
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    10 分
  • Insure the Unknown: An Executive Playbook for Transferring AI Risk with Insurance, Warranties & Bonds

    Insure the Unknown: An Executive Playbook for Transferring AI Risk with Insurance, Warranties & Bonds
    2026/02/28
    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.
    続きを読む 一部表示
    13 分
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