LFG, Datapool: The Heroes and Villains of the AI Era Are Real

By Dia Ali, Global Platforms & Solutions Leader, Data Intelligence at Hitachi Vantara

In a world rife with division, data isn’t spared. Its dual nature — a source for both good and ill — is ultimately shaped by those who interact with it. 

It can be the kryptonite that brings mega-multinationals to their knees with a blow to public trust, like Ticketmaster’s recent data breach exposing the payment information of 560 million users. Exploited as a weapon, it poses threats to privacy, security, ethical standards, and even economic and social stability. Or, it can be the lighting that fuels brilliant innovation, like the acceleration of cancer drug discovery. Indeed, data is the foundation for resilient, sustainable, and transformative new technologies like AI, driving meaningful progress around the world and empowering individuals and organizations to make better decisions. AI’s success or failure across industries is dependent on the abundance and quality of data, or lack thereof.  

Right now, the world is full of very real data heroes and data villains, the former wielding it carefully for good and the latter twisting it for chaotic ends. The people in these roles exist everywhere. They aren’t relegated to positions in data compliance and ethics offices or, alternately, the dark corners of the internet. In fact, as HBR noted, the EU in just five years “has fined companies more than 1,400 times for a total of nearly €3 billion for violations of the General Data Protection Regulation (GDPR).” Nefarious and irresponsible players can deliberately misuse data. But incomplete, inaccurate, and inconsistent data also plagues ecosystems. This so-called rogue or dirty data, like falsified and stolen data, poses risks when ignored, as overlooked records can seep into analyses and skew decision-making.  

So who are the heroes and villains shaping data and its outcomes? How are they using or abusing data systems? If we truly understand the “datapool” pantheon, we can ensure that principled innovation prevails.

Data scientists and analysts v. data manipulators and overloaders

The real-world heroes and modern innovators who turn raw data into valuable insights are data scientists and analysts. They utilize advanced analytics, machine learning, and statistical techniques to uncover hidden patterns, drive decision-making, and fuel breakthroughs across industries. They engage in practices that keep data reliable. For example, data validation can leverage automated testing and scripts to check data for anomalies and inconsistencies before analysis. And regular data profiling enables them to understand and validate its structure, content, and quality. 

Transparent reporting is key too. Data scientists and analysts achieve this by implementing version control for data scripts and reports, which helps track changes. Reproducible analysis bolsters transparency as well. By using notebooks like Jupyter and R Markdown, they can clearly document and share steps in analyses. These heroes navigate vast datasets, create and use interactive data visualizations, select appropriate algorithms, and interpret AI models. In doing so, they help ensure data quality, drive research and development forward, and solve real-world business problems.

Their villainous counterparts include data manipulators who warp and misconstrue data to present misleading conclusions, causing harm through biased or fraudulent analysis, and data overloaders who bury key insights in excessive and irrelevant data, leading to analysis paralysis and decision-making delays.

With respect to AI in particular, data scientists and researchers battle bias instigators who deliberately or carelessly introduce prejudice and noise into datasets, skewing results and undermining the integrity of research, and black box manipulators who obscure the workings of AI models, creating opaque systems that lack transparency and accountability.

IT administrators v. system saboteurs and silo isolationists

IT admins are the custodians of data infrastructure. They configure, operate, and manage diverse backend services and data sources, facilitate data discovery, and integrate AI technologies into existing systems, creating a robust foundation for data-driven initiatives. Everything they do ultimately helps protect data integrity and quality. 

They are pitted against system saboteurs who disrupt data management systems, causing data corruption, loss, or inaccessibility. Virtuous IT admins also have to face down data silo architects who impede data discovery and collaboration across an organization by creating isolated data silos. Moreover, they fight off data access blockers — the zealots who unnecessarily restrict or complicate access to data and systems for those who legitimately need it, leading to operational inefficiencies and delays in data-driven tasks.

Line of business owners v. data liquidators, change resistors, and dark data demons

On the business battlefront are heroes who align data initiatives with business goals. These line of business owners optimize resource allocation, measure the impact of data-driven projects, and manage organizational change to foster a data-driven culture. 

Data liquidators can thwart their efforts and slow an organization’s momentum at a time it should be increasing. These villains underfund or deprioritize data initiatives, hindering innovation and competitive advantage. Likewise, change resistors oppose data-driven transformations, creating barriers to the adoption of new practices and technologies. And especially vexing are the dark data demons — sometimes people, but often inefficient processes — that result in collected data remaining unused and forgotten. That leads to missed opportunities and untapped potential because valuable insights end up lost in a morass of unused data.

Nevertheless, line of business owners have powerful gear at their disposal, such as: strategic roadmaps that link data initiatives to desired business outcomes in specific, methodical, and concrete ways; stakeholder engagement in planning data strategy; change management tools and training and incentive programs to champion data-driven culture; and data strategy platforms that integrate business intelligence (BI) for strategic alignment.

Data privacy advocates v. data breachers and exploiters

Fighting the good fight across both business and government are data privacy advocates, the guardians of individual rights and liberties — as well as finances and identity. They work tirelessly to ensure that data is collected, stored, and used ethically and responsibly, protecting personal privacy and fostering trust in digital systems. They know the score as data breachers capitalize on vulnerabilities to access and misuse personally identifiable and sensitive information, compromising privacy and security — most recently with the AT&T breach, RockYou2024 10B passwords leak, Ticketmaster data breach, OpenAI’s data breach, and United Health data breach, among many others that don’t make headlines, but cause real damage.

In tandem with the breachers are the villainous data exploiters, who use personal data for unauthorized purposes, often for financial gain or unethical profiling, and shady data brokers who compile, package, and sell off personal data, often unchecked by any authority.

Technology innovators v. tech disruptors and data hoarders

Perhaps the heroes most visible to the tech sector and general public alike are the technology innovators who pioneer cutting-edge solutions. They leverage data to create transformative technologies that enhance lives, drive social progress, and solve complex challenges. Defenders of open standards and protocols, they champion interoperability, collaboration, and open-source community contributions.  

Sometimes posing in the role of innovator, but diametrically opposed to it in reality, are destructive tech disruptors. They deliberately and carelessly disrupt technological advancements, causing failures and exploiting weaknesses in new systems. They also can form dangerous alliances with data hoarders, who monopolize data access and inhibit innovation by limiting data availability to only a few privileged entities.

Others in the pantheon

Other important heroes and villains in the data universe are squaring off daily. Compliance and legal professionals serve as the custodians of data governance. They fight regulation evaders, ethics neglectors, and data breachers. By establishing policies, navigating regulatory landscapes, addressing ethical concerns, and mitigating legal risks, they ensure data practices adhere to laws and standards. 

Data stewards ensure that data assets are well-managed and used appropriately. They oversee data governance practices, maintain metadata, and ensure data integrity and compliance, while data integrity disruptors try to corrupt and manipulate metadata and data assets to undermine data quality and governance efforts.

Not least, data engineers, who build robust data pipelines and design, construct, and maintain the systems that ingest, process, and store data, work tirelessly to ensure the availability and quality of data for analysis and decision-making. Pipeline disruptors foil this good work with poor orchestration, messy dependencies, performance bottlenecks, and ungraceful systems failure.

If you know your enemy … 

In The Art of War, Sun Tzu famously warned: 

“If you know the enemy and know yourself, you need not fear the result of a hundred battles. If you know yourself but not the enemy, for every victory gained you will also suffer a defeat. If you know neither the enemy nor yourself, you will succumb in every battle.”

Understanding who is championing ethical and innovative data practices and what exactly they do — along with identifying and addressing their destructive alter egos — is a prerequisite for harnessing the full, constructive potential of data. It’s up to everyone who touches data to model heroic behavior and the tactics that safeguard it and minimize risk. If we know ourselves and our enemy, we empower a present and future where data is the foundation for innovation and driving force for good.  

Dia Ali is a visionary leader in Data Intelligence Solutions at Hitachi Vantara. With a proven track record of pioneering innovation and delivering customer-centric excellence, Dia has consistently led teams to define requirements and deliver transformative solutions for enterprises.

Dia’s remarkable journey in data intelligence has included key leadership positions at renowned companies like General Electric, Ford Motor Company, ATT, and other industry giants. Dia’s passion for mentoring and inspiring others within the organization has been a driving force throughout their career.

Holding dual bachelor’s degrees in computer engineering and automatic control systems from the prestigious University of Yarmouk in Jordan, Dia blends academic depth with practical experience to excel in the realm of data intelligence.

With an innovative mindset and an aptitude for identifying emerging trends, Dia leads Hitachi Vantara’s technology initiatives, leveraging emerging technologies, and AI to drive efficiency and excellence. They are at the forefront of creating seamless field experiences, optimizing processes, and elevating our organization’s technological capabilities. Dia is committed to shaping the future of data intelligence.