Ethics

Don’t trust AI? How to allay fears and build trust in AI tools

Originally written for Inside HR

AI is changing the way businesses operate, however, effective design and consumption frameworks need to be created and implemented in order to allay fears and build trust in AI tools.

You don’t have to venture too far into the realm of HR technology to discover the rapid growth of AI tools silently influencing decision making, providing newly discovered insights and simply making things easier to do. Whether this is analysing candidate facial expressions or voice tones during an interview, examining individual network and collaboration habits for leadership potential, monitoring employee fatigue signals or spotting who is likely to exit your company, AI is changing the way we operate.

But do we trust AI outcomes? And I mean the collective ‘we’, both HR professionals administering these tools as well as applicants and employees who are the AI subjects.

In July 2019, I ran a snap poll via LinkedIn to test general perceptions. Let me at the outset declare this would likely not pass academic requirements of a well-designed and administered survey, but LinkedIn is a global business-focused platform and the results provide a reasonable reflection of this cohort.

The initial question on trusting AI shows 61 per cent of respondents have partial to serious concerns trusting AI outcomes. A further 25 per cent of respondents registered complete or strong disagreement, and there was nobody who completely trusted AI outcomes.

Of course, one could argue that trust is like pregnancy, you can’t be half-pregnant, so if you don’t fully trust something, you essentially distrust it. We should, however, look past this binary perspective and understand that respondents are expressing their uncertainty towards something that is largely an unknown entity. People are concerned, but not necessarily against it.

As an HR or business professional, when 3 out of 5 people are not supportive of AI, it’s not something you should likely ignore. From an HR perspective, you could be losing good candidates and alienating top talent. There is plenty of newsworthy evidence about AI bias, AI decision failure and even fake AI results to warrant concern.

One of the fundamental criticisms of AI outcomes is the inability to explain the answer.

In the same poll, we asked respondents if they would trust AI outcomes more if the reasoning was visible. A whopping 92 per cent agreed or strongly agreed. While this is good news, the reality for most HR professionals is they will be unable to do this. Most HR tools using AI are commercial off-the-shelf products, producing commoditised AI answers. If it’s a true AI tool, it needs lots of data, more than you probably have of your own. The algorithms sit in a ‘black box’ and even if you could access the code, understanding how the answer is reached is complex.

“One could argue that trust is like pregnancy, you can’t be half-pregnant, so if you don’t fully trust something, you essentially distrust it”

This is why the third question in the survey – having an AI code of ethics, is so important. Close to 50 per cent of respondents scored at top scale on this question. There is a significant amount of good work evolving in this space. Many governments, technology giants and private companies are discussing and developing important principles. Some of the key focus areas include concepts such as ‘transparent AI’ and ‘white-box’ development which will increase credibility by allowing answers to be explained. Other areas are independent algorithm auditing, validated unbiased training data and developers using open-source methods and code.

AI will become a powerful solution to many of our business problems. But while it’s in its infancy, we need to build effective design and consumption frameworks in order to allay fear and build trust in these tools.

Key takeaways: HR and AI

  • Three out of five people don’t trust AI outcomes. As HR professionals we need to look for ways to address applicants and employee concerns.
  • Most AI tools used in the HR space are commercial off-the-shelf products. They may use some of your data, but the results are based on other data that you know little about.
  • If you are using AI tools in HR, ensure you declare this to users and find ways to explain how the tools got to an answer
  • In the future, applicants your suppliers and government agencies will ask you to show them your AI code of ethics. If you use AI, you should start working on this.

5 STEPS TO BOOSTING DIGITAL HR LITERACY & TRANSFORMATION

Upskilling and introducing new competencies into HR will help ensure digital transformation initiatives succeed, writes Rob Scott

Original article published by Inside HR Magazine (Feb 2016)

Given a digital workplace is undeniably the future we are rapidly heading towards, the skills any future employee will need to be effective and remain market-competitive is an important consideration for HR and talent managers. HR functions have had first-hand experience of resistance from executives to hand over strategic accountability, mainly because their business skills and acumen have been lacking.

The HR function is not immune to the disruption of modern technology; in fact, the advent of Cloud and SaaS technologies in the HR space is ahead of many other business functions. It’s an advantage that HR leaders should capitalise on to secure the relevance of the function in a digitally minded work environment.

Being digitally literate for HR is a prerequisite for the next wave of business transformation. So what are the competencies, knowledge areas and behaviours required to ensure HR professionals can deliver optimised future service? I have identified five focus areas, each of which houses a number of different subsets.
Digital HR literacy

1. Computer and platform literacy
This competency area is often mistaken as the equivalent of digital literacy. Rather, this skill set is a predecessor of digital and includes understanding how desktop PCs, laptops, smartphones and tablets work. This includes how these systems are best consumed and how they connect, and managing software applications. For many, these are skills associated with IT specialists. These skills are no longer an IT domain but have become general business skills which form a fundamental base to foster digital innovation and creativity.

2. Data design and ethics
These two components may seem like distant cousins, but how and what data we collect and derive is both a powerful business opportunity as well as one that borders on intrusion, invasion of privacy and manipulation. This skill set involves an understanding of other disciplines such as marketing and finance, as well as how things such as graphics, video, Internet of Things (IoT) feeds and other non-transactional data are integrated and designed to produce evidence-based outcomes.

3. Analytics
Analytic skills are closely aligned with data design and ethics. It’s far more than producing quality outputs, which is increasingly becoming a science in itself, and has a strong emphasis on ensuring the right information is being analysed and interpreted to inform business- and people-related decisions. Just as HR faced rebuke by becoming pseudo psychologists with off-the-shelf psychometric assessments, this skill set is embedded in formal data-science education.

4. Social intelligence
Social tools are ubiquitous and increasingly straddle our private and work lives. Understanding how search, content and social media work together requires technical understanding such as SEO as well as strategic alignment and tactical execution skills. Creating, observing and responding activities are reliant on a creative mindset, communication, writing and PR skills.

5. Innovative mindset
SaaS solutions as well as hardware are continuously being updated and improved, to the extent that new features are being “dropped” by the vendors every few months. Ignoring new features and capabilities for extended time periods is not a good strategy; rather, HR should embrace an agile and continuous improvement approach to its operating model. Skills relevant to support innovation include novel, critical & adaptive thinking, problem solving and design concepts.

Most seasoned HR professionals won’t fall into the “digital native” category, meaning that many of these concepts will be foreign and confronting. However, upskilling and introducing new competencies into the HR function will ensure digital transformation initiatives are executed with insight and purpose.

The scope of digital HR literacy

  • The next wave of business transformation will develop around the creation of a digital work ecosystem.
  • Being digitally literate is not the same as being computer literate. It’s about understanding the creation, consumption, management, manipulation and interpretation of information across multiple platforms to achieve business goals.
  • HR should capitalise on their lead in Cloud and SaaS technology deployments to further develop their digital skill sets and influence.
  • Some digital literacy skills – such as being computer literate – are general competencies; others such as data analysis are specialist skills supported by formal qualifications.
  • Digital skills should be spread across many HR roles, rather than thinking they are inherent in a single individual.