New Survey on AI Projects: Biases in Data Hamper Successful Implementation of AI in Organizations

AI Biases Negatively Impact Adoption of AI ML Capabilities; Alation “State of Data Culture” Report Reveals Barriers in Adopting Artificial Intelligence and AI Biases that Produce Discriminatory Result

AI Biases are hurting the chances of successful adoption of AI capabilities within the organization. The old axiom “garbage in, garbage out,” is a key concern as enterprises ramp their Artificial Intelligence initiatives. According to the new quarterly Alation State of Data Culture Report out today, 87% of respondents say data quality issues are a barrier to a successful implementation of AI in their organizations, with 46% saying they are very or extremely concerned. The report also found that just 8% of the data professionals surveyed say AI is being used across their organizations; 68% say AI is being used in some parts of the business.

Produced by Wakefield Research for Alation, the leader in enterprise data intelligence solutions, the Alation State of Data Culture Report provides a quarterly assessment of the progress enterprises have made in creating a data culture, the challenges they face in embracing data-driven decision-making, and the progress they have made in leveraging data to drive business value.

Among other key findings in the report:

• Inherent bias creates risk. 87% percent say that inherent biases in data being used in AI produce discriminatory results, creating risk for organizations. Solutions to this risk include:

  • Better modeling skills among analysts (42%)

  • Better curation and governance (38%)

  • Better literacy and understanding of data (38%)

  • Collecting data from more and more varied sources (36%)

  • Cataloging data for visibility (35%)

  • Core diversity in employees (35%)

  • Ability to crowdsource information (35%)

  • Stricter scrutiny of outcomes (33%)

• Innovation and efficiency are primary drivers. When it comes to deploying AI, improving and innovating products and services is the top driver (43%), followed by improving operational efficiency (33%), and improving the customer experience (24%).

• Skills are not the issue — executive buy-in, is. 55% say getting buy-in from executives who control funding for AI is a bigger obstacle to using AI effectively than employees without skills to create AI models (45%).

• Data quality issues are paramount. The top data quality issue to solve is inconsistent standards across data collection (50%), followed by compliance/privacy issues (48%), and lack of democratization or access to data (44%).

• Success factors are many. Of organizations that have deployed AI, respondents cited better modeling skills among analysts (44%), cataloging data for visibility and access to available data (38%), and ability to crowdsource info (38%), as ways to combat bias in AI. 31% say that incomplete data is a top data issue that leads to AI failing.

“We found that respondents were highly concerned about bias in AI and that data-driven organizations are better equipped to address it,” said Aaron Kalb, Co-Founder and Chief Data & Analytics Officer, Alation. “It was interesting to see data curation, data literacy, and data cataloging cited as ways to combat bias in AI as they’re also key features of organizations with data cultures. This latest report shows making investments in those areas has ethical as well as business benefits.”

Data Culture Index

The Alation State of Data Culture Report also contains the Data Culture Index (DCI). DCI is a quantitative assessment of how well an organization is positioned to enable data-driven decision-making. Enterprises were scored based upon the adoption of the three-pillar disciplines of data culture:

• Data Search & Discovery — enabling users to find what they need

• Data Literacy — properly analyzing, interpreting, and drawing conclusions from data

• Data Governance — ensuring trustworthiness and accountability of data assets, including compliance with policies and regulations

Additional key findings:

• Fewer than 20% of respondents report that their companies have fully enabled the three disciplines of data culture across all departments in the new study.

• 37% of top-tier data culture companies were more likely to exceed their revenue goals versus 28% overall, showcasing a link between data culture and revenue.

• 92% of top-tier data culture companies are also more likely to have a corporate initiative to become more data driven, compared to 69% overall.

• Breaking down silos to foster a data culture – and in particular, increasing collaboration between the data & analytics team and business units, was far more common at top-tier date culture companies (58%) than it was overall (46%).

The Alation State of Data Culture Report is a quarterly study sponsored by Alation and executed by Wakefield Research. Wakefield Research conducted a quantitative research study among 300 Data & Analytics Leaders at enterprises with 2,500+ employees in the US, UK, Germany, Denmark, Sweden, and Norway. Enterprises are polled each quarter regarding the progress of establishing a data culture — i.e., a culture of data-driven decision making — within their organizations, the challenges they face in embracing data-driven decision making, and the progress they have made in leveraging data to drive business value for their organization.

Alation pioneered the data catalog market and today is leading its evolution into a platform for a broad range of data intelligence solutions including data search & discovery, data governance, data stewardship, analytics, and digital transformation. Thanks to its powerful Behavioral Analysis Engine, inbuilt collaboration capabilities, and open interfaces, Alation combines machine learning with human insight to successfully tackle even the most demanding challenges in data and metadata management.