Tech Transformed

Trusted AI ensures that people, data, and AI systems work together transparently to create real value. This requires a focus on performance, innovation, and cost-effectiveness, all while maintaining transparency. However, challenges such as misaligned business strategies and data readiness can undermine trust in AI systems. 

To build trusted AI, it’s crucial to first trust the data. A robust data platform is essential for creating reliable and sustainable AI systems. Tools like Teradata’s ClearScape Analytics help address concerns about AI, including issues like generative AI hallucinations, by providing a solid foundation of trusted data and an open, connected architecture.

In this episode, Doug Laney, Analytics Strategy Innovation Fellow with West Monroe Partners, speaks to Vedat Akgun, VP of Data Science & AI and Steve Anderson, Senior Director of Data Science & AI at Teradata, about trusted AI. 

Key Takeaways:

• Value creation, performance, innovation, and cost-effectiveness are crucial for achieving trusted AI.
• Trusting data is essential before building AI capabilities to avoid biases, inaccuracies, and ethical violations.
• A robust data platform is a foundation for creating trusted and sustainable AI systems.
• Generative AI raises concerns about hallucinations and fictitious data, highlighting the need for transparency and accountability.
• Teradata offers features and capabilities, such as ClearScape Analytics and an open and connected architecture, to address trust issues in AI.

Chapters:

00:00 - Introduction and Defining Trusted AI

01:33 - Value Creation and the Importance of Driving Business Value

03:27 - Transparency as a Principle of Trusted AI

09:00 - Trusting Data Before Building AI Capabilities

14:51 - The Role of a Robust Data Platform in Trusted AI

21:09 - Concerns about Trust in Generative AI

23:03 - Addressing Trust Issues with Teradata's Features and Capabilities

25:01 - Conclusion

Balancing transparency in AI systems with the need to protect sensitive data is crucial. Transparency helps build trust, ensures fairness, and meets regulatory requirements. However, it also poses challenges, such as the risk of exposing sensitive information, increasing security vulnerabilities, and navigating privacy concerns.

In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Juan Jose Lopez Murphy, Head of Data Science and Artificial Intelligence at Globant, to discuss the ethical implications of AI and the necessity of building trust with users. 

Key Takeaways:

• Companies often prioritise speed over transparency, leading to ethical concerns.
• The balance between transparency and protecting competitive data is complex.
• AI misuse by malicious actors is a growing concern.
• Organisations must educate users on digital literacy to combat misinformation.
• Confidently wrong information is often more trusted than qualified uncertainty.

Chapters

00:00 - Introduction to AI Transparency

03:03 - Balancing Transparency and Data Protection

05:57 - Navigating AI Misuse and Security

09:05 - Building Trust Through Transparency

12:03 - Strategies for Effective AI Governance

As organisations adopt AI, data literacy has become more critical than ever. Understanding data—how it's collected, analysed, and used—is the foundation for leveraging AI effectively. Without strong data literacy, businesses risk making misguided decisions, misinterpreting AI outputs, and missing out on AI’s transformative benefits. By fostering a data-driven culture, teams can confidently navigate AI tools, interpret results, and drive smarter, more informed strategies.

Ready to boost your data literacy and embrace the future of AI?

Key Takeaways: 

• Companies are optimistic about ROI from AI investments.
• Data literacy is crucial for effective AI implementation.
• Technical debt poses challenges for AI infrastructure.
• Data quality and governance are essential for AI success.
• Trust in AI systems is a growing concern.
• Organizations must start with clear business priorities.
• The Data Festival will provide practical insights for AI adoption.

DATA festival is where theory meets practice to create real, actionable knowledge. This event brings together #DATApeople eager to drive the realistic applications of AI in their fields.

Leaving the hype behind, we look at the actual progress made in applying (Gen)AI to real-world problems and delve into the foundations to understand what it takes to make AI work for you. We’ll discuss when, where and how AI is best applied, and explore how we can use data & AI to shape ourfuture.

Sign up now to secure your spot

Data labelling is a critical step in developing AI models, providing the foundation for accurate predictions and smart decision-making. Labelled data helps machine learning algorithms understand input data by assigning meaningful tags to raw data—such as images, text, or audio—ensuring that AI models can recognise patterns and make informed decisions. 

AI models struggle to learn and perform tasks effectively without high-quality labelled data. Proper data labelling enhances model accuracy, reduces errors, and accelerates the time it takes to train AI systems. Whether you're working with natural language processing, image recognition, or predictive analytics, the success of your AI project hinges on the quality of your labelled data.

In this episode, Henry Chen, Co-founder and COO of Sapien, speaks to Paulina Rios Maya about the importance of data labelling in training AI models. 

Key Takeaways:

• Data labelling converts raw data into structured data that machine learning models can recognise.
• Reducing bias and ensuring data quality are critical challenges in data labelling.
• Expert human feedback plays a crucial role in improving the accuracy of AI training data and refining AI models.

Chapters:

00:00 - Introduction and Background

01:07 - Data Labeling: Converting Raw Data into Useful Data

03:02 - Challenges in Data Labeling: Bias and Data Quality

07:46 - The Role of Expert Human Feedback

09:41 - Ethical Considerations and Compliance

11:09 - The Evolving Nature of AI Models and Continuous Improvement

14:50 - Strategies for Updating and Improving Training Data

17:12 - Conclusion

Traditional KYC processes are inadequate against modern fraud tactics. While KYC helps with initial identity checks, it doesn't cover evolving threats like AI-generated deepfakes or ongoing account takeovers. 

Curious about how to protect your business from the latest threats like fake IDs, account takeovers, and AI-generated deep fakes? Tune in to our latest episode, where we dive into the essentials of full-cycle verification and real-time transaction monitoring. Find out how AI and machine learning can revolutionise your fraud detection efforts and why staying updated with regulatory changes is crucial for maintaining top-notch security. 

In this episode of Tech Transformed, Alvaro Garcia, Transaction Monitoring Technical Manager at Sumsub, speaks to Paulina Rios Maya, Head of Industry, about the manifestations of identity fraud during the user journey stages and the need for comprehensive fraud prevention measures.

Key Takeaways:

• Identity fraud manifests at different user journey stages, including onboarding and transaction monitoring.
• Businesses must implement full-cycle verification and transaction monitoring solutions to detect and prevent fraud in real time.
• AI and machine learning are crucial in analyzing suspicious user behaviour and spotting complex fraud patterns.
• SumSub offers platform solutions that include KYC, business verification, transaction monitoring, and payment fraud protection.

00:00 - Introduction and Overview

00:35 - Identity Fraud in the User Journey

02:01 - Types of Fraud and Fraud Prevention

04:20 - Real-Time Monitoring and Enhancing Systems

05:46 - Common Types of Fraud Faced by Financial Institutions

08:40 - The Challenge of AI-Generated Deepfakes

10:04 - Beyond KYC: Additional Measures for Fraud Prevention

12:29 - Prevention Measures and Synthetic Identity Fraud

15:21 - Effective Fraud Prevention Solutions

17:45 - Assessing the Effectiveness of Fraud Prevention Strategies

19:08 - Staying Up to Date with Regulatory Requirements

21:31 - Conclusion

AI is revolutionising contact centres by automating routine tasks, reducing response times, and enhancing customer experience. AI is built to handle simple inquiries efficiently and at scale. 

It helps contact centres close the gap between customer expectations and conventional customer service by enabling engagement through digital channels. AI-driven analytics improve decision-making by capturing and analysing data from customer interactions. Organisations can overcome challenges by starting small and gradually building trust in AI's capabilities. 

In this episode, Paulina Rios Maya, Head of Industry Relations at EM360 speaks to Jon Arnold, Principal at J Arnold & Associates about the use of AI in contact centres. 

Key Takeaways:

• AI is a transformative technology that rethinks customer engagement and addresses customer problems in contact centres.
• AI enables engagement through digital channels and helps contact centres close the gap between customer expectations and conventional customer service.
• AI-driven analytics improve decision-making by capturing and analysing data from customer interactions.
• Organisations can overcome challenges by starting small and gradually building trust in AI's capabilities.
• AI helps protect privacy and mitigate fraud in contact centres.

Chapters:

00:00 - Introduction and Overview

01:06 - The Transformational Power of AI in Contact Centers

03:00 - Automating Routine Tasks and Enhancing Customer Experience

06:24 - Engaging Customers through Digital Channels

11:09 - Improving Decision-Making with AI-Driven Analytics

15:28 - Overcoming Challenges and Building Trust in AI

17:23 - Protecting Privacy and Mitigating Fraud in Contact Centers

Join us in this exciting episode of Tech Transformed, where we talk to Kelly Vero, a pioneering game developer, digital leader, and visionary in the metaverse. With a career spanning 30 years and a resume that includes contributions to legendary franchises like Tomb Raider and Halo 3, Kelly brings a wealth of knowledge and experience to the table.  

Kelly’s unique journey in the tech world is nothing short of extraordinary. From joining the military to learn about ballistics for Halo 3 to founding the award-winning startup NAK3D, she has always pushed the boundaries of what’s possible. 

Kelly Vero speaks to Paulina Rios Maya about the hurdles of being a woman in the tech industry, the principles of gamification, and the overhyped trends in AI and NFTs. They discuss what’s genuinely beneficial versus what’s just noise.

Key Takeaways: 

• The gaming industry offers opportunities for problem-solving and creativity.
• Role models can come from everyday people who inspire and support others.
• Gamification is about creating an engaging user experience that encourages return and contribution.
• The tech industry has seen beneficial changes in globalized platforms and a focus on quantum solutions.

Chapters: 

00:00 - Introduction and Background

02:28 - The Gaming Industry and Problem Solving

07:36 - Challenges and Role Models in the Tech Industry

11:54 - The Principles and Ethical Considerations of Gamification

18:30 - Beneficial Changes and Overhype in the Tech Industry

20:25 - Creating Digital Objects and the NFT Standard

23:45 - Introducing NAK3D: Bringing Non-Designers into Design

Podcasts have become a valuable tool for sharing knowledge on topics like cybersecurity, AI, data management, and infrastructure. 

EM360Tech took it even further with their expertly curated content and engaging discussions featuring industry leaders and experts.

Michael Lodge, founder and CEO of EM360Tech, shares his valuable insights on the evolution of enterprise tech podcasting on Podcast Gurus by GHA Marketing.

EM360Tech, founded by Michael Lodge in 2008, is a leader in enterprise tech podcasting.

Our platform provides podcasts and digital content for IT and business leaders, discussing essential topics such as artificial intelligence, cybersecurity, data management, and infrastructure management.

Our content is made to help enterprises align their IT strategies with their business goals.

We noticed that messages are more easily conveyed through podcasts. While many enterprise tech resources are available in written form, few include interviews with people directly involved in the field.

We wanted to fill this gap by creating a podcast, making it a unique and valuable source for enterprise leaders to learn about industry trends.

Here is what we mainly cover in our podcast (among others)):

• Educational Content: Our podcasts provide insights into best practices, by industry leaders
• Comprehensive Topic Coverage: Our podcasts cover essential business and IT topics, such as Cybersecurity, AI, Data, Infrastructure Management, and Emerging Technologies.
• Interview of Experts, by Experts: Our podcasts engage with leading industry analysts and experts to offer thought leadership and unbiased insights.

Our unique approach to podcasting is that we do not have only one host. We actually have multiple, based on the topic of the interview. 

We indeed found out that expertise requires experts. Which is why every interview is led by an industry expert analyst to make sure our audience learns from the best.

This provides a balanced view from both vendor and user perspectives, offering listeners a comprehensive understanding of each topic.

The format and frequency of our podcast episodes are critical in maintaining listener engagement.

Each episode ideally lasts 20-25 minutes, ensuring detailed discussions without losing interest. Regular publishing with multiple episodes weekly keeps our content fresh and relevant.

We have seen enterprise tech podcasting evolve from a niche medium into a significant networking and business development tool. 

Initially embraced by those in tech and digital media, our podcasts have become platforms for in-depth discussions on complex topics like AI, cybersecurity, and data management. 

Our format allows for clear and engaging presentations, making it easier for listeners to understand and absorb information.

• Audience Engagement: Our podcasts attract listeners interested in the discussed subjects, providing a direct line to a targeted audience.
• Speaker Effectiveness: We ensure that our speakers are engaging and knowledgeable, making the content relatable and digestible.
• Interactive Format: Seeing and hearing our speakers adds a layer of engagement that text alone cannot match.

Our transition from traditional print media to digital formats was motivated by the necessity for cost-effective and extensive global distribution. 

As publishing physical magazines became increasingly challenging both financially and logistically, we found digital platforms like podcasts to be viable alternatives.

This shift also supports our environmental goals by reducing paper use and working towards carbon neutrality.

Effective content distribution strategies are essential for engaging our audience and driving traffic to our primary digital platforms.

Our content is primarily hosted on a dedicated platform where additional resources and community interactions enhance the user experience.

Spreading our content across various channels extends its reach. Detailed listener analytics are crucial for crafting targeted marketing strategies and understanding audience behavior.

Leveraging Podcasts for Engagement

Podcasts are powerful platforms for building relationships and establishing our brand authority, particularly in industries where buying decisions require careful consideration.

For those planning to launch a podcast, focusing on engaging content with knowledgeable hosts and guests is essential.

Selecting a clear, relevant topic that resonates with our audience and testing it with pilot episodes ensures our podcast effectively reaches its target audience and fosters engagement.

At EM360Tech, enterprise tech podcasting is pivotal for tech industry leaders. Our platform provides essential insights that align IT strategies with business goals.

The shift from print to digital media has expanded the reach and efficiency of content distribution, supporting our environmental and economic objectives.

Podcasts are essential for keeping abreast of technological advancements and industry trends, ensuring our listeners stay informed and ahead in their field.

Keywords: enterprise tech podcasting

Meta Description: Explore the growth of enterprise tech podcasting and learn how platforms like EM360 Tech are shaping the future of digital media.

Strategic choices with significant implications mark Latin America's approach to AI. Many countries in the region have adopted AI technologies and frameworks developed by leading tech nations, focusing on imitation rather than innovation. This strategy enables rapid deployment and utilisation of advanced AI solutions, bridging the technological gap and fostering economic growth. 

However, reliance on external innovations raises questions about the region's long-term competitiveness and ability to contribute original advancements to the global AI landscape.

In this podcast, Alejandro Leal, Analyst at KuppingerCole, speaks to Paulina Rios Maya, Head of Industry Relations, about how socio-economic factors, including limited research funding, infrastructural challenges, and the need for quick technological catch-up drive this pattern of imitation. While this approach has led to swift AI adoption, it underscores a dependence on foreign technologies and expertise.

Key Takeaways: 

• Trust, ethics, and legal considerations are essential challenges in integrating AI into the security infrastructure.
• Public-private partnerships and regional cooperation are crucial for advancing AI technology in the region.
• Interoperability and alignment with international and regional standards are key areas of focus to ensure the ethical use of AI in Latin America.

Chapters:

00:00 - Introduction: AI in Latin America

00:58 - Key Initiatives in the Security Sector in Mexico

05:12 - Mexico's Evolution in National Security

07:33 - Challenges in Integrating AI into Security Infrastructure

12:40 - Comparison with Other Latin American Countries

19:26 - The Role of Public-Private Partnerships

22:51 - Focus on Interoperability and Alignment with Standards

23:46 - Conclusion: Ethical Use of AI in Latin America

AI fraud is not just a concern, it's a pressing issue. As artificial intelligence technologies advance, fraudsters are developing increasingly sophisticated methods to exploit these systems. Typical forms of AI fraud include deepfakes, which use AI to create convincing fake images, audio, or videos for disinformation, blackmail, or identity theft, and advanced phishing schemes that leverage AI to craft highly personalized and deceptive messages. Addressing and understanding AI fraud is not just crucial, it's urgent for individuals, businesses, and governments to protect against these evolving threats. 

Join Alejandro Leal and Pavel Goldman-Kalaydin, Head of AI and Machine Learning at Sumsub, as they delve into the growing issue of AI fraud.

Themes:

• AI fraud
• Deepfakes
• Global trends
• Regulation

Chapters:

00:00 - Introduction and Background

01:13 - Understanding AI Fraud

02:11 - Examples of AI-Driven Fraud

08:02 - Global Trends in AI-Driven Fraud

13:55 - Preventing AI-Driven Fraud

18:11 - The Future Evolution of AI Fraud

22:38 - Conclusion and Final Thoughts