PPAP Training course, Production Part Approval Process Training discusses the requirements, procedures and protocols, and practices and activities specified by the PPAP manual.

Through this PPAP training, students prepare a sample PPAP package for submission, from the beginning to the end.

What is PPAP?

Production Part Approval Process (PPAP) is an analysis management to measure the capability of the system. Once the PPAP protocol is obeyed, the number of dysfunctional parts will reduce down to below a handful per million parts produced. This conclusive process will evaluate the performance of all the processes and steps involved in producing parts and it will assure that all the specifications and requirements are met.

This process assesses how well the processes used to produce parts will meet the specifications. Participants who complete this course They also know how to conduct and evaluate the processes, and

Added Value of the PPAP Training:

• Learn how to evaluate a PPAP report
• Review and prepare PPAP forms
• Learn how to submit PPAP reports
• Discuss the specific needs for part approval records or sample retention
• Know when/where PPAP submissions are required
• Recognize various levels of PPAP submission
• Understand where and how the PPAP submissions can be incorporated into the APQP
• Understand the statistics of process capability, process capability index, performance capability, and performance capability index (Cp, Cpk, Pp, and Ppk.)
• Learn how to present the outcomes to the customer in a high-qualified format align with the customer’s expectation.

TONEX PPAP Training Will Also Cover:

• The concepts and principals of the PPAP
• All the components of PPAP
• Review all the required documentation for each submission level
• Real-life examples and case studies

TONEX PPAP Training Methodology

TONEX PPAP training course is in the form of an interactive workshop. The seminar includes many in-class activities including hands on exercises, case studies and workshops. During the PPAP training course, students can bring in their own sample projects and through our coaching, develop their own PPAP.

Audience

Production Part Approval Process Training, PPAP Training is a 2-day course designed for:

• Internal auditors
• Second-party auditors
• The ISO/TS 16949 implementation team
• Cross-functional team members
• Project Managers, Engineers and Quality Department Personnel
• All individuals involved in submitting PPAP report
• All individuals involved in product quality planning activities
• All individuals interested in learning more about PPAP

Training Objectives

Upon the completion of PPAP training course, the attendees are able to:

• Understand the goals and objectives of PPAP
• Understand the phases of PPAP
• Explain why PPAP is applied
• Discuss all components of the PPAP
• Understand the customer specific requirements for submitting PPAP
• Discuss the evidence required by customers to submit PPAP
• Complete all phases and steps of a PPAP
• Define the scope and purposes of the PPAP
• Follow all the PPAP submission levels
• Evaluate all PPAP reports
• Prepare and fill out PPAP forms
• Understand how to incorporate the PPAP submissions into APQP
• Articulate and discuss the results of the PPAP

Course Outline

Overview of PPAP

• PPAP definition
• The purpose of PPAP
• When is a PPAP required?
• Benefits of PPAP submission
• What are the elements of a PPAP submission?
• What are the levels of PPAP?
• What is “Significant Production Run”?
• Run @ Rate
• Definition of risk
• PPAP status
• Authorized Engineering Change Documents

PPAP Requirements

• AIAG requirements
• Design Records
• Engineering Change Documents
• Customer Engineering Approval, if required
• Design Failure Modes & Effects Analysis (DFMEA) Process Flow Diagram
• Process Failure Modes & Effects Analysis (PFMEA) Control Plan
• Measurement Systems Analysis (MSA) Dimensional Results
• Qualified Laboratory Documentation
• Appearance Approval Report (AAR)
• Sample Product
• Master Sample
• Checking Aids
• Customer-Specific Requirements
• Part Submission Warrant (PSW)
• Internal, costumed, requirements

PPAP Levels

• Level 1 – Warrant only and Appearance Approval Report as requested submitted to the customer
• Level 2 – Warrant with samples and limited supporting data submitted to the customer
• Level 3 – Warrant with product samples and complete supporting data submitted to customer
• Level 4 – Warrant and other requirements as defined by the customer
• Level 5 – Warrant with product samples and complete supporting data reviewed at the supplier’s manufacturing location
• PPAP level table
• New parts levels
• Part changes levels

Production Warrant

• Definition
• Purpose
• When to use it
• Reviews checklist

Process Flow Diagram (PFD)

• What is PFD
• Purpose
• Symbols
• PFD example
• Reviewers checklist

Process FMEA (PFMEA)

• Origin of FMEA
• Definition
• Objectives
• When to use it
• Steps of PFMEA procedure
• Ratings
  • Severity
  • Occurrence
  • Detection
• Analyzing the results
• PFMEA exercise

Control Plan

• Definition
• Purposes
• Application
• Tool interaction
• Phases
• Process, tools, characteristics
• Specifications, Measurement, Sample Size & Frequency
• Control Method, Reaction Plan

Measurement Style Analysis (MSA)

• Definition
• Objective
• Application
• Who needs to be involved?
• Attribute
• Variable
• Observed variation
• Resolution
  • Error in resolution
  • Possible causes
• Repeatability
• Reproducibility
  • Error in resolution
  • Possible causes
• Gage R&R study
• Gage R&R steps

1. Select 10 items that represent the full range of long-term process variation
2. Identify the evaluators
3. Calibrate the gage or verify that the last calibration date is valid
4. Record data in the Gage R&R worksheet in the PPAP Playbook
5. Have each appraiser assess each part 3 times (trials – first in order, second in reverse order, third random)
6. Input data into the Gage R&R worksheet
7. Enter the number of operators, trials, samples and specification limits
8. Analyze data in the Gage R&R worksheet
9. Assess MSA trust level
10. Take actions for improvement if necessary

• Gage R&R case study
• Reviewer’s checklist

Dimensional Results

• What is it?
• Objectives
• When is it applied?
• Acceptance criteria
• Reviewer’s checklist

Material & Performance Test Results

• Material test results
• Module test results
• Performance test results

Initial Process Study

• Definition
• Purposes
• Applications
• Steps for Determining Process Capability

1. Choose the product or process characteristic
2. Validate the specification limits
3. Validate the measurement system
4. Collect data
5. Analyze data characteristics
6. Analyze process stability
7. Calculate process capability

• Variable data
• Capability indices
  • CpK
  • PpK
  • Cp vs CpK
• Reviewer’s checklist

Appearance Approval Report

• Definition
• Objective
• Application
• Sample report

Sample Production Parts

• Definition
• Purpose
• Application
• Labeling
• Part label example

Completing the PPAP Submission

• Electronic submission
• Element 1 Part Submission Warrant
• Element 2 Design Records and & Bubbled Part Prints
• Element 3 Approved Engineering Change Documentation
• Element 4 Customer Engineering Approvals
• Element 5 Design FMEA (DFMEA)
• Element 6 Process Flow Diagrams
• Element 7 Process FMEA (PFMEA)
• Element 8 Control Plan
• Element 9 Measurement System Analysis (MSA)
• Element 10 Dimensional Report
• Element 11 Material, Performance Test Results
• Element 12 Initial Process Study (Cpk/Ppk)
• Element 13 Qualified Lab Documentation
• Element 14 Appearance Approval report
• Element 15 Sample Parts
• Element 16 Master Sample
• Element 17 Checking Aids
• Element 18A Tooling Information Form
• Element 18B Packaging Form 

Discussion for Successful Implementation

TONEX Hands-On Workshop Sample PPAP

• Choose one case to conduct a PPAP on
• Prepare all the elements of the report
• Prepare required forms for submitting PPAP
• Use data to provide specific requirements for part approval records and sample retention
• Go through all the PPAP levels
• Perform required statistics analysis including Cp, CpK, or PpK
• Ensure the submission meet the customer’s specific requirements
• Present your final report to an imaginary customer

Battery Energy Storage Systems (BESS) Essentials: Engineering, Management, Testing, Safety, Reliability, and Maintenance is a 2-day course that offers a comprehensive exploration of Battery Energy Storage Systems (BESS) covering engineering principles, management strategies, testing methodologies, safety protocols, reliability considerations, and maintenance practices. Participants will gain a holistic understanding of BESS technologies and their applications in various industries.

Learning Objectives:

1. Gain a thorough understanding of Battery Energy Storage Systems (BESS), including components, configurations, and operational principles.
2. Develop skills in designing, implementing, and managing BESS installations for diverse applications.
3. Learn testing methodologies and protocols for assessing BESS performance, safety, and reliability.
4. Understand safety measures, regulatory compliance, and risk management strategies for BESS.
5. Enhance knowledge of BESS maintenance practices, troubleshooting techniques, and lifecycle management.

Target Audience:

• Engineers involved in the design, development, and integration of BESS systems.
• Managers and decision-makers responsible for BESS project planning, implementation, and optimization.
• Testing and quality assurance professionals focusing on BESS performance evaluation and validation.
• Safety and compliance officers ensuring regulatory adherence and risk mitigation in BESS installations.
• Reliability engineers and technicians responsible for maintaining BESS reliability and uptime.

Course Agenda:

Day 1: BESS Fundamentals and Engineering

• Introduction to Battery Energy Storage Systems (BESS): components, types, and applications.
• Engineering principles of BESS: design considerations, sizing, and integration with renewable energy sources.
• Grid integration and control strategies for BESS: frequency regulation, peak shaving, and demand response.
• Case studies and best practices in BESS engineering for different industries and use cases.

Day 2: Management, Testing, Safety, Reliability, and Maintenance

• Project management for BESS: planning, procurement, implementation, and performance monitoring.
• Testing methodologies for BESS: performance testing, safety testing, environmental testing, and reliability testing.
• Safety protocols and risk management strategies for BESS installations.
• Reliability engineering for BESS: failure modes, maintenance strategies, predictive maintenance, and uptime optimization.
• Regulatory compliance, standards, and certifications for BESS.
• Case studies, group discussions, and hands-on exercises on BESS testing, safety, reliability, and maintenance.

Delivery Format: The course will be delivered through a blend of lectures, interactive workshops, case studies, demonstrations, and group discussions. Participants will have access to simulation tools, testing equipment, and industry experts to facilitate practical learning and skill development in BESS engineering, management, testing, safety, reliability, and maintenance.

Upcoming course: CSSSP Level 1 (Specialist)

• Length: 4 Days
• When: August 19-22 2024 (Live Online)
• Where: Dallas, TX.

Learn more >>>

Certified Space Security Specialist Professional (CSSSP): Level 1

We are developing an overwhelming reliance on space technology – a trend not lost on cybercriminals.

This growing dependency on satellites and the like, puts organizations in a precarious position. In industries like transport and logistics, location data is routinely recorded in real time from GPS satellites and sent to back offices to allow teams to track drivers and assets.

Organizations which have remote outposts or oceangoing ships can’t exactly get online via a mobile or cable network, so they have to use communications satellites instead. On top of that, satellites store sensitive information they collect themselves, which might include images of sensitive military installations or critical infrastructure.

Of course all of these factors make for attractive targets to various types of cybercriminal. Although residing in the vacuum of deep space makes them less vulnerable to physical attacks, space-based systems are still ultimately controlled from computers on the ground. At issue is that data is transmitted by and stored on orbiting satellites more and more every year. Therefore, bad actors have them in their sites due to the high value of data stored on satellites and other space systems.

Particularly disturbing, space security specialists now tell us that cyber attackers don’t even need to be expert hackers from space-faring nations. And neither do they need direct, physical access to control systems belonging to organizations like NASA, ESA or Roscosmos.

For NASA, reliable communication between ground and spacecraft is central to mission success, especially in the realms of digital communication (data and command links). Unfortunately, these light communication links are vulnerable to malicious intrusion. If terrorists or hackers illegally listen to, or worse, modify communication content, disaster can occur.

Especially worrisome are the consequences of a nuclear powered spacecraft under control of a hacker or terrorist, which could be devastating. Obviously, all communications to and between spacecraft must be extremely secure and reliable.

Military satellites and space systems are also vulnerable since almost all modern military engagements rely on space-based assets, providing GPS coordinates, telecommunications, monitoring and more. Aging IT systems, supply-chain vulnerabilities and other technological issues that leave military satellite communications open to disruption and tampering also need to be addressed according to space security personnel.

While navigational satellite systems like GPS (US), GLONASS (Russia) and Beidou (China) might not be the easiest targets to hack, there are dozens of other satellite owners of global communications. Additionally, thousands more companies rent bandwidth from satellite owners for selling services like satellite TV, phone and internet. Then there are hundreds of millions of businesses and individuals around the world which use them.

All told, it’s a pretty large potential attack surface which is connected directly to the internet.

Certified Space Security Specialist Professional (CSSSP) Course by Tonex

Although some of these issues are no different from other industries, space systems are met with a unique confluence of cybersecurity risks that complicates the sector’s remediation capabilities.

Governments, critical infrastructure and economies rely on space-dependent services—for example, the Global Positioning System (GPS)—that are vulnerable to hostile cyber operations. However, few space-faring states and companies have paid sufficient attention to the cybersecurity of satellites in outer space, creating a number of risks.

Accelerate your space cybersecurity career with the CSSSP certification.

Certified Space Security Specialist Professional (CSSSP) certification is ideal for space and security practitioners, analysts, engineers, managers and executives interested in proving their knowledge across space security practices and principles.

The CSSSP® (Certified Space Systems Security Professional) qualification is one of the most respected certifications in the space security industry, demonstrating an advanced knowledge of space cybersecurity.

Earning the CSSSP proves you have what it takes to effectively design, implement and manage a cybersecurity space program. With a CSSSP, you validate your expertise and become a Space Cyber member, unlocking a broad array of exclusive resources, educational tools, seminars, conferences and networking opportunities.

CSSSP certification also explores factors that led to the space sector’s poor cybersecurity posture, various cyberattacks against space systems, and existing mitigation techniques employed by the sector.

Analyzing the current state of the industry along with security practices across similar sectors, several security principles for satellites and space assets are proposed to help reorient the sector toward designing, developing, building and managing cyber secure systems. These security principles address both technical and policy issues in order to address all space system stakeholders.

Prove your skills, advance your career, and gain the support of a community of cybersecurity leaders here to support you throughout your career.

The CSSSP qualification has been developed and maintained jointly by SpaceCyber.org and Tonex.

CSSSP Domains (CBK) are:

1. Space Systems Engineering
2. Cybersecurity Principles for Space Systems
3. Space Cybersecurity Foundation
4. Space Security Planning, Policy and Leadership
5. Space Security Architecture and Operation
6. Space Threat and Vulnerability Analysis and Assessment
7. Space Ethical Hacking, Penetration Testing and Defenses
8. Space Intrusion Detection Analysis
9. Space Network Penetration Testing and Ethical Hacking
10. Space Embedded Systems Cybersecurity
11. Space Defensible Security Architecture and Engineering
12. Space Forensic Analysis
13. Space Network and System Reverse Engineering
14. Space Incident Response and Network Forensics
15. MIL-STD-1553 Cybersecurity
16. ARINC 429 Cybersecurity
17. Artificial Intelligence(AI), Machine Learning (ML) and Deep Learning (DL) Integration with Space Cybersecurity
18. Blockchain Integration with Space Cybersecurity
19. Sensor Fusion Integration with Space Cybersecurity
20. Electronic Warfare Capabilities in Space
21. Use of Electromagnetic Pulses or Directed Energy (laser beams or microwave-bombardments)
22. Space System Survivability and US War Fighting
23. Electronic Warfare and Aircraft Survivability
24. Cyber Warfare Capabilities in Space Missions
25. Counter Communications System
26. Electronic and Cyber Warfare in Outer Space
27. Counter-space Capabilities
28. Types of Counter-space Technology
29. Measures and Their effectiveness in Addressing Counter-space Capabilities

For more information, questions, comments, contact us. 

Future related programs to Certified Space Security Specialist Professional (CSSSP) Certification are:

• Space Cyber Infrastructure Specialist (SCIS)
• Space Cyber Engineering Specialist (SCES)
• Space Cyber Operations Specialist (SCOS)
• Space Cyber Technology Professional (SCTP)
• Space Cyber Operations Manager (SCOM)
• Space Cyber Infrastructure Expert (SCIE)
• Space Cyber Domain Expert (SCDE)
• Space Cyber Manager (SCM)
• Space Cyber Authority Expert (SCAE)
• Space Cyber Application Specialist (SCAS)
• Space Cyber Leadership Certificate (SCLC)

Certified AI Ethics and Governance Professional™ (CAEGP™) Certification is a 2-day course where participants gain a deep understanding of AI ethics principles and frameworks as well as learn to assess and manage ethical risks associated with AI implementations.

—————————-

AI Ethics and Governance professionals play a critical role in ensuring that AI technologies are developed and deployed in a responsible, ethical, and accountable manner.

By establishing ethical guidelines, promoting transparency and accountability, addressing issues of fairness and equity, and advocating for responsible AI policies, AI Ethics and Governance professionals help shape the future of AI in a way that benefits society as a whole.

AI Ethics and Governance professionals are responsible for addressing issues of fairness, equity, and inclusivity in AI systems. This involves identifying and mitigating biases and discrimination in AI algorithms and datasets, as well as ensuring that AI technologies are accessible and inclusive for all individuals and communities.

By championing fairness and equity, AI Ethics and Governance professionals help promote social justice and equality in the use of AI technologies.

Additionally, AI Ethics and Governance professionals play a key role in advocating for responsible AI policies and regulations. This includes engaging with policymakers, industry stakeholders, and civil society organizations to shape AI governance frameworks that prioritize ethical considerations and protect the rights and interests of individuals.

By advocating for responsible AI policies, AI Ethics and Governance professionals help ensure that AI technologies are deployed in a manner that maximizes their benefits while minimizing potential harms.

AI Ethics and Governance professionals play a vital role in promoting transparency and accountability in AI development and deployment. This includes advocating for open and transparent AI algorithms and decision-making processes, as well as establishing mechanisms for auditing and monitoring AI systems for compliance with ethical standards and regulatory requirements.

By promoting transparency and accountability, AI Ethics and Governance professionals help build trust and confidence in AI technologies among stakeholders and the public.

Certified AI Ethics and Governance Professional™ (CAEGP™) Certification Course by Tonex

Public Training with Exam: Septmber 3-4, 2024

The Certified AI Ethics and Governance Professional™ (CAEGP™) Certification Course by Tonex is a comprehensive program designed to equip professionals with the knowledge and skills needed to navigate the ethical and governance challenges posed by Artificial Intelligence (AI). This course delves into the intricate intersection of technology, ethics, and governance, providing participants with a holistic understanding of responsible AI practices.

This CAEGP™ Certification Course by Tonex is a comprehensive program designed for professionals seeking to navigate the complex intersection of artificial intelligence, ethics, and governance. This course equips participants with a deep understanding of AI ethics principles, frameworks, and risk assessment. Delving into regulatory landscapes and compliance requirements, it empowers individuals to develop and implement effective AI governance strategies.

The program addresses societal impacts, ensuring responsible AI deployment. Ideal for AI professionals, data scientists, and policymakers, the CAEGP™ course imparts the necessary knowledge and skills to foster ethical and responsible AI practices, culminating in a valuable certification.

Learning Objectives:

• Gain a deep understanding of AI ethics principles and frameworks.
• Learn to assess and manage ethical risks associated with AI implementations.
• Acquire skills to develop and implement effective AI governance strategies.
• Explore regulatory landscapes and compliance requirements related to AI.
• Understand the societal impact of AI and strategies for responsible deployment.
• Attain the CAEGP™ certification, validating expertise in AI ethics and governance.

Audience: This course is ideal for AI professionals, data scientists, business leaders, policymakers, and anyone involved in AI development, deployment, or decision-making. It caters to individuals seeking to enhance their knowledge of AI ethics and governance to ensure responsible and sustainable AI practices.

Pre-requisite: None

Course Outline:

Module 1: Introduction to AI Ethics and Governance

• Evolution of AI Ethics
• Foundations of AI Governance
• Key Drivers for Ethical AI
• Role of Governance in AI Ecosystems
• Ethical Considerations in AI Decision-making
• Industry Best Practices in AI Governance

Module 2: AI Ethics Principles and Frameworks

• Core Ethical Principles in AI
• Utilitarianism and Deontology in AI Ethics
• Application of Ethical Frameworks in AI Development
• Case Studies on Ethical Dilemmas in AI
• Emerging AI Ethics Standards
• Integrating Ethical Considerations into AI Project Lifecycles

Module 3: Risk Assessment and Management in AI

• Identifying Ethical Risks in AI Projects
• Ethical Implications of Bias and Fairness in AI
• Ethical Challenges in AI Decision Systems
• Strategies for Mitigating Ethical Risks
• Ethical Considerations in AI Research and Development
• Monitoring and Adapting Ethical Guidelines Throughout AI Project Lifecycles

Module 4: Developing AI Governance Strategies

• Building Effective AI Governance Structures
• Establishing AI Ethics Committees
• Integrating AI Governance into Organizational Frameworks
• Aligning AI Governance with Corporate Values
• Ensuring Accountability in AI Decision-making
• Continuous Improvement of AI Governance Strategies

Module 5: Regulatory Landscapes and Compliance

• Global AI Regulatory Frameworks
• Legal and Ethical Considerations in AI Compliance
• Navigating Privacy and Security Regulations in AI
• Ensuring Transparency in AI Systems
• Ethical Compliance Audits in AI
• Challenges and Opportunities in Adhering to AI Regulations

Module 6: Societal Impact and Responsible AI Deployment

• Analyzing Societal Implications of AI
• Ethical Considerations in AI for Social Good
• Strategies for Responsible AI Deployment
• Community Engagement in AI Development
• Ethical Considerations in AI Marketing and Communication
• Assessing and Communicating the Social Value of AI Projects

Course Delivery:

The course is delivered through a combination of lectures, interactive discussions, hands-on workshops, and project-based learning, facilitated by experts in the field of AI Ethics and Governance. Participants will have access to online resources, including readings, case studies, and tools for practical exercises.

Assessment and Certification:

Participants will be assessed through quizzes, assignments, and a capstone project. Upon successful completion of the course, participants will receive a certificate in AI Ethics and Governance.

Capstone Project: Building a framework for Responsible AI development and deployment

Building a framework for Responsible AI development and deployment, ensuring that AI technologies are used ethically, fairly, and for the benefit of society while minimizing potential risks and challenges.

• Technology Overview:
  • AI technology encompasses a range of techniques such as machine learning, deep learning, natural language processing, and computer vision. These technologies enable machines to learn from data, recognize patterns, make decisions, and perform tasks that traditionally required human intelligence.

• Gotchas:
  • There are several challenges or “gotchas” associated with AI ethics and governance. These include biases in data and algorithms, lack of transparency in AI systems, potential job displacement due to automation, privacy concerns with data collection, and the misuse of AI for harmful purposes like surveillance or misinformation.

• Ethics/Responsible AI:
  • Ethics in AI refers to the principles and guidelines that govern the development, deployment, and use of AI systems in a responsible and ethical manner. This includes fairness and accountability in algorithmic decision-making, transparency in AI systems, privacy protection, and ensuring AI benefits society.

• Controls Considerations:
  • Controls in AI governance refer to the mechanisms and policies put in place to manage and mitigate risks associated with AI technologies. This includes implementing fairness and bias detection tools, establishing data governance practices, ensuring compliance with regulations such as GDPR or CCPA, and developing robust cybersecurity measures to protect AI systems from malicious attacks.

• Oversight, Metrics Considerations:
  • Effective oversight and metrics are crucial for monitoring and evaluating AI systems’ performance, impact, and adherence to ethical standards. This involves establishing governance bodies or committees responsible for AI oversight, defining key performance indicators (KPIs) to measure AI effectiveness and ethical compliance, conducting regular audits and assessments, and fostering collaboration between stakeholders including policymakers, industry experts, researchers, and civil society organizations.

Exam Domains

• Foundations of AI Ethics: Core ethical principles and their application in AI technologies.
• AI Governance: Frameworks and best practices for overseeing AI systems, including transparency and accountability.
• Regulatory Compliance: Detailed understanding of global and regional laws affecting AI development and deployment.
• Risk Management: Strategies for identifying, assessing, and mitigating ethical risks in AI projects.
• Stakeholder Engagement and Policy Making: Techniques for engaging with stakeholders and shaping policies that govern AI use.

Number of Questions

• Total Questions: 60 questions.

Type of Questions

• Multiple-Choice Questions (MCQs): To test knowledge on ethics, governance, and compliance.
• Essay Questions: To assess the ability to articulate complex ideas and propose solutions for ethical dilemmas in AI.
• Case Studies: Real-world scenarios requiring application of ethical principles and governance strategies.

Exam Duration

Duration: 3 hours. Online any time, Open Books

Additional Details

• This certification would target professionals such as AI ethics officers, compliance managers, and policymakers in technology sectors.
• A passing score might be set at around 75%, emphasizing a strong understanding and ability to apply ethical and governance principles.
• The exam should be available in multiple formats, including online for global accessibility and in-person in a controlled, proctored environment to ensure integrity.
• This proposed exam structure aims to ensure that certified professionals are not only knowledgeable about theoretical aspects of AI ethics and governance but are also capable of effectively implementing these principles in diverse and complex environments.