trust

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.

9 Exciting Trends and Opportunities in HR for 2019

Grateful to  Orlando Imperatore : Flickr 2018

Toss away the crystal ball!  Of course there is no rational way to ‘predict’ what will be important for HR leaders and business execs in 2019. In almost every case, each organisation is on a unique journey of people transformation, technical empowerment, culture mind-shift or simple operational improvements.

So my list is a collection of stuff which I’ve happened to engaged HR and other leaders about in the last 12 months and which was being considered for future plans. Perhaps only 1 is of interest to you, maybe all 9 – It doesn’t really matter. 

Here we go! and in no particular order

  1. PA – Personal Analytics 
    • HR Analytics has become an important tool for supporting organisational decision making around people. But it tends to support the employer more than the employee. As we see Employee Engagement, Happiness and changes in the Workforce and Workplace take center stage, there is a gaping hole around providing individuals with Personal Analytics in order for them to make better personal and business related decision within a continually fast-paced and constantly changing work environment.
  2. Trust
    • As we see new technologies such as Chat-bots, Robotic Process Automation, Machine learning Algorithms, Personal data-sharing and Tracking cozying up next to  human workers, the trust relationship which underpins so many things in our organisations is being diluted. The need is not just about building trust in technologies which are performing ‘human-like’ tasks or gathering our data, but effectively managing the implications for functions such as HR who have custodianship over some of these new-age tools. 
  3. Non-Exec Talent Coach 
    • Executive coaching is a mature offering, but as the nature of work and the variety of relationships between an organisation and a worker develop  ( I don’t want to say employee, because many are not technically that), the need for Independent Development Coaches at  lower levels, and which is not funded by the employer is being sought. Some of this demand exists because younger talented individuals do not want to mirror the behavior of current leaders (Think about many current Bank Leaders…. not a good model to follow), but want to become the best version of themselves without company influence.
  4. Beyond Engagement
    •  I’ve never been a fan of culture or engagement surveys – statistically they are full of errors and often based on pop-psychology. However listening with ‘Data Ears’ is becoming more relevant. In other words understand the mood of the company, or Engagement levels (Customer or Employee) or Happiness levels by analyzing the data trail left by employees, customers, your supply chain seems far more reliable and less prone to typical survey inaccuracies. 
  5. Personal Data Repository
    • One of my favorites. I’ve been engaging on this topic for a number of years. But with the changing workforce landscape, the growing contingent and gig enthronements, workers want the ability to store their own work history (think mini HR system), including Learning records, Pay and Benefit data, Performance scores, basic biographics, Job and Position history. They want control over their own data, and the ability to share it and withdraw it easily with an employer. This is not your typical Linkedin profile BTW. Big opportunity for HR Software vendors.
  6. Communication
    • Not necessarily new, but becoming an area of focus again as organisations get lost if their digital and technology transformation activities. Humans are irrational, make mistakes and are not perfect. Technology, with all its benefits, has the ability to create sterile and perfect environments, which are not conducive to human productivity or happiness. Making sure we don’t capitulate our responsibility to communicate to machines/technology is important. 
  7. The Science of HR 
    •  HR is actually a lot more complex that most people realize. Often the individual HR activities are not complex (some can be though), but ensuring there is alignment across a multitude of interrelated HR activities is where the real complexity lies, and where things often go wrong. Underpinning all HR decisions is the level of HR Maturity. When HR activities are not executed based on the Maturity level, you typically get Executive despondency towards HR or frustrated HR leadership. 
  8. Instant answers to HR Tech
    • The fast-paced and continuously changing work environments are demanding HR and IT leaders make quick, but informed HR Technology buying decisions. Gone of the days that it takes 4-8 months to do a traditional RFP, only to discover the new SaaS tools you were considering have significantly changed. There are some great services, analysts and tools available to speed up these decisions.
  9. HR Operating Model Change 
    • Many organisations are realizing the traditional Dave Ulrich HR operating model needs some adaptation. Not a radical change (as it is mostly still working), but a focus change to ensure the operating model can support ‘speed and agility’ needs of modern organisations. Changes include the ‘Business Partner’ reaching into the customer and supply chain world, the ‘Centre of Excellence’ (CoE) becoming a Networking Management Function and the ‘Shared Service Centre’ transforming into a Digital Data Centre.

That’s it!. And why not 10 I hear you ask, no reason, I only had 9 to share. Whats the point of making stuff up 🙂