STRASYS SOLUTIONS SDN BHD or STRASYS | SSM Company Registration Number: 200801017496 (818789-D) | is a rapidly growing company providing diversified consultancy services in Malaysia and abroad.  It started in 2008 with its main office in Jalan Klang Lama, Kuala Lumpur, MALAYSIA. STRASYS is all about strategic management and integrated systems solutions. Through determined thinking of innovation, we’ve developed and implemented outcome-based models and essential tools with adorable results.

“We Care for Your Strategic Reasons to Exist, Grow, Excel and Sustain”

...is our tagline, and STRASYS develops insightful leaders and followers who are groomed to be passionate professionals, passionate enough to challenge the status quo for a better tomorrow. STRASYS has the proper fundamentals with perfectly customized tools to trigger corporate ownership and a sense of belonging and jump-start the drive towards innovations empowered with the right attitude, knowledge, skills, talents, and ideas to create corporate excellence.

While Artificial intelligence (AI) is truly a revolutionary feat of computer science and sets to become the core component of all modern software over the coming years and decades with lots of business opportunities, there is also an inherent risk to it; a risk which we now call as the Artificial Intelligence Bias (AIB)

Artificial Intelligence (AI) Bias has become a prominent concern as society increasingly relies on AI systems to make critical decisions across various industries, from finance and healthcare to criminal justice and employment.

STRASYS has developed a complete audit framework

Artificial Intelligence Bias Risk Audit (AIBRA)

AIBRA audits / assesses AI related biases in your management and operational systems and in that ensure your AI driven services and products are responsible and ethical in every sense of the phrase.

Contact us or attend our training (3 levels) to know more about this solution:-

Be A Trained Personnel / Assessor / Auditor

Audit Findings & Reporting of AIBRA using DATARUSH® Framework

Basic Level (2 days):
(no prerequisite prerequisites)

Introduction

This training program provides participants with a comprehensive understanding of AI bias, ethical considerations, and responsible AI development and deployment. It also delves into analytic-based thinking (ABT), risk-based thinking (RBT), and introduces the AIBRA using the DATARUSH® Framework. Participants will learn how to assess and mitigate AI bias risks effectively.

Course Objectives:

The intermediate-level course is tailored to empower participants to:

  • Understand the fundamentals of AI technology, its prevalence across industries, and the implications of AI bias.
  • Identify and analyze different forms of AI bias and their impact on decision-making processes.
  • Explore ethical considerations related to AI development, deployment, and usage, including fairness, transparency, and accountability.
  • Learn best practices for responsible AI development, including data collection, model training, and algorithmic decision-making.
  • Develop skills in analytic-based thinking (ABT) to evaluate AI systems objectively and critically.

Course Methodology:

The approach taken for this intermediate level training combines theoretical instruction with active, hands-on exercises. Participants will engage in:

  • Interactive lectures to discuss advanced concepts.
  • Case studies to apply knowledge to real-world scenarios.
  • Group workshops to plan and simulate various stages of the audit process.
  • Role-playing exercises to understand different stakeholder perspectives.
  • Presentations and debates to refine communication and critical thinking skills.

Target Audience:

This program is aimed at professionals such as AI ethics officers, data scientists, compliance managers, and IT auditors who are responsible for overseeing AI implementations and are committed to fostering responsible AI practices.

Target Industry:

While the program is industry-agnostic, it is especially relevant to sectors heavily involved in AI technologies, such as tech corporations, financial services, healthcare providers, and manufacturing firms.

Training Schedule

Day one (9 – 6pm)

  • Recap of Basic Level Training
  • Introduction to Intermediate Level
  • Practical application of the DATARUSH® framework Understanding audit objectives
  • Planning for an AI Bias audit (also covering Level of Automation & Data Mobility).
  • Identifying potential bias in specific AI solutions.
  • Developing and implementing customized bias mitigation strategies using AIBRA using DATARUSH® Framework

Day Two (9 – 6pm)

  • Why, and what is an Audit?
  • Types of Audit
  • What makes an audit meaningful?
  • Outputs and outcomes of an audit
  • Audit process of AIBRA using DATARUSH® Framework
  • Roles and responsibilities
  • Plan an Audit using the AIBRA using DATARUSH® Framework
  • Presentation and discussion on checklists and audit plans
  • Conducting an audit
  • Opening Meeting simulations
  • The importance of communication

Closure

Participants will be exposed to the foundational concepts, including an introduction to AI, understanding AI bias, ethical considerations, and responsible AI development and deployment and they will gain practical skills in conducting AI bias risk audits and developing strategies to ensure AI systems are fair, ethical, and reliable.

Intermediate Level (2 days):

(2 days of BASIC LEVEL as its prerequisite)

Introduction

This two-day INTERMEDIA training session is cantered on Audit Findings & Reporting using the AIBRA with DATARUSH® Framework, following up on four days of foundational (BASIC 2 Days) and intermediate (2 Days) training. The course will guide participants through the final stages of AI Bias auditing, from briefing top management and discussing on-site audit results to completing assessments and formulating mitigation plans. Additionally, it explores the broader implications of AI in society and reinforces the principles of ethical and responsible AI development.

Course Objectives:

The intermediate-level course is tailored to empower participants to:

  • Master the practical application of the DATARUSH® framework in real-world scenarios.
  • Gain a comprehensive understanding of audit objectives within the context of AI.
  • Plan and conduct AI Bias audits, considering the intricacies of Level of Automation and Data Mobility.
  • Identify potential biases in AI systems and develop bespoke strategies to address them.
  • Engage in productive discussions about different types of audits and what constitutes a meaningful audit.
  • Learn the roles and responsibilities involved in the audit process.
  • Foster effective communication skills through opening meeting simulations and presentations.

Course Methodology:

The approach taken for this intermediate level training combines theoretical instruction with active, hands-on exercises. Participants will engage in:

  • Interactive lectures to discuss advanced concepts.
  • Case studies to apply knowledge to real-world scenarios.
  • Group workshops to plan and simulate various stages of the audit process.
  • Role-playing exercises to understand different stakeholder perspectives.
  • Presentations and debates to refine communication and critical thinking skills.

Target Audience:

This program is aimed at professionals such as AI ethics officers, data scientists, compliance managers, and IT auditors who are responsible for overseeing AI implementations and are committed to fostering responsible AI practices.

Target Industry:

While the program is industry-agnostic, it is especially relevant to sectors heavily involved in AI technologies, such as tech corporations, financial services, healthcare providers, and manufacturing firms.

Training Schedule

Day One

  • Recap of Basic Level Training
  • Introduction to Intermediate Level
  • Practical application of the DATARUSH® framework Understanding audit objectives
  • Planning for an AI Bias audit (also covering Level of Automation & Data Mobility).
  • Identifying potential bias in specific AI solutions.
  • Developing and implementing customised bias mitigation strategies using AIBRA using DATARUSH® Framework

Day Two

  • Why, and what is an Audit?
  • Types of Audit
  • What makes an audit meaningful?
  • Outputs and outcomes of an audit
  • Audit process of AIBRA using DATARUSH® Framework
  • Roles and responsibilities
  • Plan an Audit using the AIBRA using DATARUSH® Framework
  • Presentation and discussion on checklists and audit plans
  • Conducting an audit
  • Opening Meeting simulations
  • The importance of communication

Closure

Participants completing this intermediate training will leave with a fortified skillset in AI Bias auditing, ready to apply their knowledge towards promoting ethical AI within their organisations.

Advance Level (2 days):

(2 days of BASIC + 2 days of INTERMEDIATE Level training as its prerequisite)

Introduction

This advanced two-day training session is cantered on Audit Findings & Reporting using the AIBRA with DATARUSH® Framework, following up on four days of foundational (BASIC 2 Days) and intermediate (2 Days) training. The course will guide participants through the final stages of AI Bias auditing, from briefing top management and discussing on-site audit results to completing assessments and formulating mitigation plans. Additionally, it explores the broader implications of AI in society and reinforces the principles of ethical and responsible AI development.

Course Objectives:

The advance-level course is tailored to empower participants to:

  • To effectively brief and communicate audit findings to top management.
  • To analyze and interpret results from on-site AI Bias audits.
  • To complete on-site assessments using the AIBRA with DATARUSH® Framework.
  • To develop and present comprehensive audit reports and dashboards.
  • To devise actionable mitigation plans and solutions for identified AI biases.
  • To engage in closing meeting simulations to enhance communication and reporting skills.
  • To discuss the future of AI, focusing on bias mitigation and the technology's role in solving societal issues.
  • To reinforce the principles of ethical and responsible AI in all aspects of development and deployment.

Course Methodology:

The course uses a variety of advanced teaching methods, including executive briefings, live case study discussions, in-depth workshops, reporting simulations, and strategy development sessions. It features collaborative group activities, participant-led presentations, and simulated closing meetings to provide an environment that mimics real-world scenarios.

Target Audience:

This course is exclusively for those who have successfully completed the two-day basic and intermediate training sessions. It is specifically designed for senior data scientists, AI auditors, compliance officers, business unit managers, and C-suite executives involved in overseeing and implementing AI technologies within their organizations.

Target Industry:

The advanced training is highly relevant to industries actively engaged in AI technology and innovation, such as high-tech corporations, financial institutions, healthcare providers, e-commerce platforms, and manufacturing companies. These sectors require a keen understanding of AI bias and its impacts on society to steer AI applications towards positive outcomes responsibly.

Training Schedule

Day One

  • Briefing on the finding to the Top Management of an organization
  • Discuss Results of on-site audit (Audit teams divided into Business Units at a selected Enterprise)
  • Complete on-site assessment using AIBRA using DATARUSH® Framework.
  • Reporting and Follow up
  • Audit findings and Interpretation
  • Audit report and Dashboard (LOA, DM & AIBR)
  • Mitigation plans and solutions

Day Two

  • Closing meeting simulations
  • Future of AI and bias mitigation.
  • The role of AI in solving societal issues and promoting responsible AI development
  • Closing Remarks: “Ethical & Responsible AI” Reinforced

Closure

The advanced training is highly relevant to industries actively engaged in AI technology and innovation, such as high-tech corporations, financial institutions, healthcare providers, e-commerce platforms, and manufacturing companies. These sectors require a keen understanding of AI bias and its impacts on society to steer AI applications towards positive outcomes responsibly. This advanced course emphasizes a strategic perspective on AI Bias auditing and its crucial role in shaping future AI applications. It's intended for those deeply involved in the ethical dimensions of AI and who are in a position to influence AI strategy within their organisations.

Be also introduced to our next
REAL SUSTAINABLE "GREEN"
SUPPLY CHAIN INNOVATION TECHNOLOGY
| 4FOLD |

Be introduced to 4FOLD (developed by Holland Container Innovations; HCI)
& STRASYS
(Corporate partner of the Chartered Institute of Logistics and Transport Malaysia; CILT)
is championing HCI's visionary business
here in this region (South East Asia; SEA)

LET THERE BE LIGHT WHEN THERE IS NO LIGHT
(Green energy tiles and granules to reduce heat map and carbon emission to the environment)

 

Is your organization CAPITALIZING on the right data & its analytics?

GET THE COMPREHENSIVE INDUSTRY 4.0 DATA CAPITALIZATION ASSESSMENT  REPORT NOW.....

 

“DATARUSH” is all about the “rush” (fast and furious movement / mobility) of “data” within and across organizations involving other entities within a bigger eco-system.

“DATARUSH” is about the dynamism of data to enhance the profitability and sustainability of businesses today especially within the Industry 4.0 environment.

“DATARUSH” is all about realizing the critical INTELLIGENCE for organizations to exist, grow and excel vibrantly….


In short...

DATARUSH© helps organizations to thrive in the Industry 4.0 Environment

...facilitates new mode of thinking for organizations to identify the key stumbling blocks towards profitability,

...identifies modes of wastages within the organization (as a whole and also departmentally)

....diagnoses root-causes related to non-technical component of the systems in place (i.e; human errors, behaviarioul issues and leadership challenges)....


Be Assessed &.....

● Get to understand how EXISTING SYSTEMS within the ECO-SYSTEM influence BUSINESS PERFORMANCE

● Get to know if ORGANISATIONAL DATA and its analytics are aligned to CORPORATE ASPIRATIONS

● Get to dive into CORE CHALLENGES and surface out ACTIONABLE SOLUTIONS

● REALIZE SUPER teams by challenging the “SILOS”

● FORTIFY LEADERSHIP potentials for greater performances

STRASYS SOLUTION SDN BHD is dedicated in partnering our clients to provide innovative and diversified solutions.

We address your Industry 4.0 (I4.0) challenges with focus on delivering results in 3 key areas:

Strategic Management || Integrated IT Solutions || Virtual Learning & Development