Algorithms and machine learning are often applying the same bias and prejudices that humans show, however many people are failing to notice as their attention is elsewhere.
Today’s priority can become yesterday’s issue with simply a new line of code. By the time people notice, the game may be over. Even if someone wanted to correct the system, biases may become so buried they are almost invisible and hard to detect.
An example of this is many organisations spend time, money and energy assisting people to recognise unconscious bias in the workplace through webinars and workshops. This is almost a yesterday’s solution when algorithms are making employment decisions written by predominately young male developers. It is this group, which may not even be employed directly by the company that can transfer their unconscious biases to the algorithm. This is today’s reality.
A sentencing algorithm created in America highlights this. It predicted which people would re-offend after an initial crime. The algorithm falsely said black offenders would offend twice as often as white offenders. The people who were creating the algorithm was predominately white males.
Developers may also be directed to create algorithms that meet specific company requirements which may be biased. If this practice exists, algorithms may be considered trade secrets and are not required to be divulged.
In California, a person was jailed for life based on a piece of software that relied on DNA traces from a crime scene. When the defence asked to see the source code of the algorithm it was denied because it was called a trade secret.
If anyone was convicted of a crime by the information provided by an algorithm, wouldn’t it be their human right to know how the decision was made? Apparently not yet.
Organisations must take notice of the emerging issues with the use of algorithms. Where possible, the methodology used must be visible and transparent. What is the alternative?
Although algorithms are becoming more sophisticated they are not the Holy Grail. Many capable people will simply not fit the algorithm irrespective of bias. Though underestimating the speed at which algorithms are evolving would not be wise. It is espoused that they can detect gender and race by scanning a resume with an 88% accuracy.
In Australia, today it is not possible for an applicant to challenge an algorithm’s decision about the suitability of their application. The process prevents this. The applicant submits their CV online, they subsequently receive an anonymous computer generated an acknowledgement.
If unsuccessful they get another computer-generated response giving no real reason. The whole process is invisible to the applicant and leaves only the applicant’s imagination to understand why.
Even without intent, if the process itself not managed properly may entrench a range of inequalities as previous examples demonstrate. This is very thing many institutions have spent years trying to avoid.
It is easy to imagine that an algorithm may be coded to a specific group. Like an expert from a specific school or country within a certain age bracket. It is not beyond the realms of possibility, particularly if it is a trade secret and there are no rights of appeal.
This scenario helps breed inequality and if history has taught us anything, inequality sews the seeds of societal discontent, often with catastrophic consequences.
As priority decisions made by algorithms must become more visible for both practical and ethical reasons. Imagine if technology could tell the applicant applying for the job, why they did not get it, how the decision was made, and what they could do to increase their opportunities. The impact could be positive for the company’s brand and its ethical approach may help attract talent to their business.
Countries like Germany have created guidelines which provide algorithm visibility. They state that “if an accident is unavoidable the self-driving car must not make any choices over who to save. No decisions should be made on age, sex, race, disabilities, and so on; all human lives matter”.
Statesmen like cosmologist Stephen Hawking and Tesla CEO Elon Musk have endorsed a set of principles that reinforce the importance of transparency to ensure that self-thinking machines remain safe and act in humanity’s best interests.
Not every leader has the knowledge available to them that some countries or technologists do. However, today’s leaders have a responsibility to be informed and have enough knowledge to ask the probing and ethical questions. Otherwise, they will be implementing yesterday’s solutions.
The relationship with technology and bias is only one of the complex ethical issues that are facing society today. It becomes even more complex if the system is invisible to the people using it or being affected by it. The power cannot lie solely with the algorithm. Today’s mantra must be algorithm transparency.
The technological revolution is speeding up. By 2030 the consequences of this disruption will make the world we live in and the jobs we perform almost unrecognisable.
Look beyond the driverless automobile and consider the impact of 1 billion working drones.
Preparation is required to skill, reskill and upskill Australians to meet the opportunities and challenges the revolution will deliver.
I often catch public transport around cities to meet with various clients. Recently as I sat gazing out the window, I realised that there was a growing disconnect about what I was observing and the economic information that I had been gathering.
The cities were vibrant. There appeared no expense on developing skyscrapers, apartment complexes, and supporting infrastructures. People appeared busy, dressed in reasonable clothes, drinking plenty of coffee, talking in cafes and lunching in restaurants.
These observations were similar, but obviously different in my own local community.
What played on my mind was how can there be such an appearance of affluence when economic data was indicating that many Australians financial positions were deteriorating?
The data indicated that Australian households has one of the highest level of debt in the world. Admittedly much of the debt is considered good debt because it has the potential for income generation.
You are fifty something and you are advised that your services are no longer required by an almost faceless being. Your gut is in a knot and you can hardly breathe…the first thought is financial…your second thought is… what the hell do I do know?
Everyone knows how difficult it is to get another job. You sit trapped in the chair as you listen through a fog of redundancy rhetoric. Phrases like: “This is an opportunity for a new start” “You have two days of outplacement to help you write your CV”. It feels like the words roll off a faceless cold mechanical tongue, reading cold mechanical scripts in a sculptured body devoid of compassion. Perhaps it feels like that because in that moment, everyone is dealing with the discomfort, by dissociating from each other.
I was asked to deliver of Future of Work series with Annie Gaffney on ABC radio.
It was over a period of three months during 2017.
This is an outline of the final session
The population is growing, less people are dying, jobs are changing from full time to contract and at the same time more machines are doing both mind and muscle work… and of course technology is speeding up.
Historically Human Resources (HR) has had limited opportunity to set the people management agenda. It is a function that has primarily prospered when the economy, or an industry sector is booming and obtaining and attracting staff is a priority. HR’s subsequent value often regresses in economic downturns, when labor becomes more abundant.
The modern-day example is the growth in the technology sector, and its requirements for talent.
“Tech companies such as Google, Microsoft, and Apple are now on the front lines of HR innovation, largely because they have an acute need for specialized talent. Human capital is practically their only major asset; talent is in short supply; and competitors are eager to lure employees away”. HBR
HR’s historical fluctuating value, has an opportunity to reposition itself, as a critical strategic function with the ongoing development of People Analytics. This methodology has primarily evolved along with the rise of the Tech industry.
I want you to imagine the image of an average prosperous Australian adult. They have a job, they have a home, a means of transport, a family, they can afford to go out for a meal, and go on a holiday. There is plenty of fat on their metaphoric bones.
If for some reason the family loses part of their income capability, they have some money in the bank for a rainy day, may have a redundancy payout, or can rely on other family members to obtain work. There are plenty of opportunities to store food in the pantry.
For many Australians, this is a reality, for others an aspiration, and for others an impossibility. However, if you look at the trend data in Australia, that image of the prosperous Australian is starting to waver with many living on the edge in significant debt. They may still be able to live a prosperous life style however, they can’t afford anything to go wrong.
“What lies between most people and destitution is their job”
Satyajit Das Financial Commentator
Most working Australians families including the tax office have relied on regular salaried incomes. This however is unlikely to be the primary employment model in the future. Instead many workers will be “off balance” sheet. They will be self-employed, contract labour or outsourced.
The future of work is more about flexibility and reducing costs. It has been turbo charged by technology and globalisation. There is no going back.
In Australia, there is already a significant reduction in full time employment and increasing trends towards flexible employment options. This is already resulting in Underemployment one of Australian’s most growing workforce concerns.
Have you heard of “dollar ready”? I recently engaged in a conversation with a business person and he said that their organisation was not employing people who were not “dollar ready”. They would employ skilled people from overseas rather than employ juniors or graduates, because they did not provide the dollars on day one. In other words, “dollar ready”.
This attitude is not shared by all but it is powerful language that makes you sit up and take notice. Complacency is not an option considering current trends.
- Youth unemployment is 13.3% and one in five are underemployed. Competition for jobs is intense.
- Graduate employment is the lowest it’s been since the 1992-93 recession.
- Apprenticeship numbers have declined since 2010.
Have you heard of the term being “dollar ready”? I recently engaged in a conversation with a business person and he said that their organisation was not employing people who were not “dollar ready”. They would employ skilled people from overseas rather than employ juniors or graduates, because they did not provide the dollars on day one.
This attitude is not shared by all businesses; however, the term “dollar ready” is evocative language. It does make you sit up and take notice, especially when you are aware of the youth unemployment trends in Australia.