Michael Wahl, MBA

Michael Wahl, MBA

Grosse Pointe, Michigan, United States
6K followers 500+ connections

About

My role as Vice President of Technology at Tweddle Group has centered around pioneering…

Articles by Michael

Contributions

Activity

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Experience

  • Tweddle Group Graphic

    Tweddle Group

    Clinton Township, Michigan, United States

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    Grosse Pointe, Michigan, United States

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    Clinton Township, MI

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    Clinton Township, Michigan, United States

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    Livonia, MI

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    Southfield, MI

Education

  • University of California, Berkeley, Haas School of Business Graphic
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    The Innovating with AI Incubator program offers an in-depth, constantly updated curriculum, complemented by a dynamic 24/7 community and hands-on live coaching from Rob Howard, who is the founder and lead instructor for the program.

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Licenses & Certifications

Volunteer Experience

  • Amazon Web Services (AWS) Graphic

    AWS Community Builder

    Amazon Web Services (AWS)

    - Present 2 years 10 months

    #AWSCommunityBuilder

  • Taproot Foundation Graphic

    Information Technology Consultant

    Taproot Foundation

    - Present 7 years

    Science and Technology

    Pro bono work, web design, other technical and business consulting.

  • Winning Futures Graphic

    Volunteer

    Winning Futures

    - Present 2 years

    Education

    Career mentoring

  • Big Brothers Big Sisters of Metropolitan Detroit Graphic
  • Information Technology Volunteer

    St. Paul on the Lake Catholic School

    - Present 6 years

    Education

  • Den leader

    Boy Scouts of America, Cub Scouts Pack 61 St. Paul On The Lake

    - Present 7 years

Publications

Projects

  • AI Framework Development

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    The framework development outlines the strategic plan for implementing AI technologies. The vision is to drive innovation, efficiency, and competitive advantage through AI. The roadmap includes several key sections:

    Business Needs: The document emphasizes aligning AI technologies with business objectives, such as enhancing operations, improving customer satisfaction, and generating new products.

    Data Availability: It highlights the importance of evaluating data preparedness and…

    The framework development outlines the strategic plan for implementing AI technologies. The vision is to drive innovation, efficiency, and competitive advantage through AI. The roadmap includes several key sections:

    Business Needs: The document emphasizes aligning AI technologies with business objectives, such as enhancing operations, improving customer satisfaction, and generating new products.

    Data Availability: It highlights the importance of evaluating data preparedness and infrastructure, including data quality, collection, storage, and management methods. The document suggests improvements to support current and future AI projects.

    Assembling the AI Team: The plan involves creating a diverse team with data scientists, AI engineers, business analysts, and project managers. It also mentions leveraging partnerships with AI vendors and academic institutions.

    Selecting the AI Tech Stack: The document discusses the need to prioritize AI technologies that align with business goals. It suggests focusing on quick wins and using a scoring approach to prioritize AI projects.

    Applications-Pilots/POCs: The roadmap includes creating and evaluating prototypes, applying agile methods for development, and focusing on transformational projects rather than just cost savings.

    Expanding AI Solutions: It proposes a strategy for expanding successful AI prototypes within the organization and setting up metrics to evaluate AI performance.

    Getting Production Ready: The document emphasizes stakeholder engagement, training, and development to prepare employees for AI tools and systems.

    AI Use Cases: It lists various AI applications with high returns and low efforts, such as customer service chatbots, generative content creation, predictive maintenance, process automation, and AI-assisted recruitment.

    This work provides a comprehensive plan for integrating AI into operations, focusing on innovation, efficiency, and strategic alignment with business goals.

  • AI Governance and Ethics Framework

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    The AI Governance and Ethics Framework outlines principles and policies for responsible AI use within an organization.

    Scope: This framework applies to all AI systems, projects, and initiatives within the organization, covering the entire AI lifecycle and involving cross-functional teams.

    AI Governance Structure: The AI Governance Committee, a cross-functional team, will oversee AI governance, developing and enforcing ethics policies.

    Committee Responsibilities: The…

    The AI Governance and Ethics Framework outlines principles and policies for responsible AI use within an organization.

    Scope: This framework applies to all AI systems, projects, and initiatives within the organization, covering the entire AI lifecycle and involving cross-functional teams.

    AI Governance Structure: The AI Governance Committee, a cross-functional team, will oversee AI governance, developing and enforcing ethics policies.

    Committee Responsibilities: The committee will review AI projects for risks, ensure alignment with policies, oversee bias detection, ensure compliance with laws, and provide ethical AI leadership.67

    Fairness and Bias: AI systems should be developed with fairness in mind, including regular bias audits, using bias mitigation tools, and employing inclusive datasets.

    Transparency and Explainability: AI models must be transparent and explainable, with built-in explainability tools, comprehensive documentation, and clear communication of AI decisions.

    Accountability and Responsibility: Clear accountability for AI systems must be established, including risk management processes and comprehensive audit trails.

    Compliance with Regulations and Data Privacy: AI systems must comply with laws and regulations, with regular audits, privacy-preserving technologies, and data governance practices.

    Monitoring and Auditing: AI systems should be monitored and audited regularly to ensure performance and compliance, with procedures for retraining models as needed.

    Ethical AI Leadership and Culture: The organization is committed to fostering a culture of ethical AI, providing ethics training, ensuring leadership commitment, and designating ethics champions.

    Governance Enforcement and Review: The AI Governance Committee will conduct regular reviews of policies, provide annual reports, and ensure alignment of AI projects with the framework before deployment.

Organizations

  • Amazon Web Services

    Community Builder

    - Present

    #AWSCommunityBuilders

  • Cloud Security Alliance

    Member

    - Present

    Detroit Chapter

  • (ISC)2

    Member

    - Present

    Greater Detroit Chapter

  • Information Systems Security Association

    Member

    - Present

    Detroit Chapter

  • AUTO-ISAC

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    - Present
  • AXELOS - ITIL

    Member

    - Present
  • Detroit Economic Club

    Member

    - Present
  • Technology Business Management

    Council Member

  • Western Governors University

    Alumni Ambassador

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