One of the questions that we at the International Data Corporation are asked is what impact technologies like Artificial Intelligence (AI) will have on jobs. Where are there likely to be job opportunities in the future? Which jobs (or job functions) are most ripe for automation? What sectors are likely to be impacted first? The problem with these questions is that they misunderstand the size of the barriers in the way of system-wide automation: the question isn’t only about what’s technically feasible. It’s just as much a question of what’s legally, ethically, financially and politically possible.
That said, there are some guidelines that can be put in place. An obvious career path exists in being on the ‘other side of the code’, as it were – being the one who writes the code, who trains the machine, who cleans the data. But no serious commentator can leave the discussion there – too many people are simply not able to or have the desire to code. Put another way: where do the legal, financial, ethical, political and technical constraints on AI leave the most opportunity?
Firstly, AI (driven by machine learning techniques) is getting better at accomplishing a whole range of things – from recognising (and even creating) images, to processing and communicating natural language, completing forms and automating processes, fighting parking tickets, being better than the best Dota 2 players in the world and aiding in diagnosing diseases. Machines are exceptionally good at completing tasks in a repeatable manner, given enough data and/or enough training. Adding more tasks to the process, or attempting system-wide automation, requires more data and more training. This creates two constraints on the ability of machines to perform work:
- machine learning requires large amounts of (quality) data and;
- training machines requires a lot of time and effort (and therefore cost).
Let’s look at each of these in turn – and we’ll discuss how other considerations come into play along the way.
Speaking in the broadest possible terms, machines require large amounts of data to be trained to a level to meet or exceed human performance in a given task. This data enables the bot to learn how best to perform that task. Essentially, the data pool determines the output.
However, there are certain job categories which require knowledge of, and then subversion of, the data set – jobs where producing the same ‘best’ outcome would not be optimal. Particularly, these are jobs that are typically referred to as creative pursuits – design, brand, look and feel. To use a simple example: if pre-Apple, we trained a machine to design a computer, we would not have arrived at the iMac, and the look and feel of iOS would not become the predominant mobile interface.
This is not to say that machines cannot create things. We’ve recently seen several ML-trained machines on the internet that produce pictures of people (that don’t exist) – that is undoubtedly creation (of a particularly unnerving variety). The same is true of the AI that can produce music. But those models are trained to produce more of what we recognise as good. Because art is no science, a machine would likely have no better chance of producing a masterpiece than a human. And true innovation, in many instances, requires subverting the data set, not conforming to it.
Secondly, and perhaps more importantly, training AI requires time and money. Some actions are simply too expensive to automate. These tasks are either incredibly specialised, and therefore do not have enough data to support the development of a model, or very broad, which would require so much data that it will render the training of the machine economically unviable. There are also other challenges which may arise. At the IDC, we refer to the Scope of AI-Based Automation. In this scope:
- A task is the smallest possible unit of work performed on behalf of an activity.
- An activity is a collection of related tasks to be completed to achieve the objective.
- A process is a series of related activities that produce a specific output.
- A system (or an ecosystem) is a set of connected processes.
As we move up the stack from task to system, we find different obstacles. Let’s use the medical industry as an example to show how these constraints interact. Medical image interpretation bots, powered by neural networks, exhibit exceptionally high levels of accuracy in interpreting medical images. This is used to inform decisions which are ultimately made by a human – an outcome that is dictated by regulation. Here, even if we removed the regulation, those machines cannot automate the entire process of treating the patient. Activity reminders (such as when a patient should return for a check-up, or reminders to follow a drug schedule) can in part be automated, with ML applications checking patient past adherence patterns, but with ultimate decision-making by a doctor. Diagnosis and treatment are a process that is ultimately still the purview of humans. Doctors are expected to synthesize information from a variety of sources – from image interpretation machines to the patient’s adherence to the drug schedule – in order to deliver a diagnosis. This relationship is not only a result of a technicality – there are ethical, legal and trust reasons that dictate this outcome.
There is also an economic reason that dictates this outcome. The investment required to train a bot to synthesize all the required data for proper diagnosis and treatment is considerable. On the other end of the spectrum, when a patient’s circumstance requires a largely new, highly specialised or experimental surgery, a bot will unlikely have the data required to be sufficiently trained to perform the operation and even then, it would certainly require human oversight.
The economic point is a particularly important one. To automate the activity in a mine, for example, would require massive investment into what would conceivably be an army of robots. While this may be technically feasible, the costs of such automation likely outweigh the benefits, with replacement costs of robots running into the billions. As such, these jobs are unlikely to disappear in the medium term.
Thus, based on technical feasibility alone our medium-term jobs market seems to hold opportunity in the following areas: the hyper-specialised (for whom not enough data exists to automate), the jack-of-all-trades (for whom the data set is too large to economically automate), the true creative (who exists to subvert the data set) and finally, those whose job it is to use the data. However, it is not only technical feasibility that we should consider. Too often, the rhetoric would have you believe that the only thing stopping large scale automation is the sophistication of the models we have at our disposal, when in fact financial, regulatory, ethical, legal and political barriers are of equal if not greater importance. Understanding the interplay of each of these for a role in a company is the only way to divine the future of that role.
Small SA town goes smartphone-only
Vodacom partners with farming business to upgrade all residents of Wakkerstroom from 2G devices to smartphones
All residents of the small town of Wakkerstroom, which straddles Mpumalanga and kwaZulu-Natal provinces, have had their 2G feature phones upgraded to 3G devices.
The initiative is a result of Vodacom partnering with BPG Langfontein, a farming business that employs the majority of the people living in Wakkerstroom. It is now the first smartphone-only town in South Africa. This is a model the network provider says it hopes to replicate across the country as part of its mission to connect people who live in deep rural areas and are still dependent on 2G networks.
Wakkerstroom, is the second oldest town in Mpumalanga province, on the KwaZulu-Natal border, 27 km east of Volksrust and 56 km south-east of Amersfoort.
“There are growing expectations for big corporates the size of Vodacom to serve a social purpose, and for us to use our resources and core capabilities to make a significant contribution in transforming the lives of ordinary people,” says Zakhele Jiyane, Managing Executive for Vodacom Mpumalanga. “We are helping to remove communication barriers, so that citizens in the area can be part of the digital revolution and reap the associated benefits. By moving the more than 1400 farm workers from 2G to 3G devices, this will also free much needed spectrum and this spectrum can be re-farmed to provide for faster networks such as 3G and 4G.
“Crucially, the move opens a new world of connectivity for farm workers in Wakkerstroom. As a result, most people in the area will now be able to use the Vodacom network to connect on the net and access online government services, eHealth services such as Mum&Baby and eCommerce. Learners can now surf the internet for the first time and access Vodacom’s eSchool free of charge and those who are actively looking for jobs can start using their smartphones and tablets to apply for jobs over the internet on Vodacom’s zero-rated career sites. This will be key for driving growth to the benefit of people living in this area.”
Vodacom has already deployed 4G base stations in Wakkestroom as part of this initiative.
For the next phase of this project, says Vodacom, it is going to educate the farm workers about data and the benefits of the Internet. Vodacom will also look at various ways in which it can help empower members of this community in areas of education, gender-based violence and health.
Facebook fact-checking goes to 10 more African countries
Facebook today announced the expansion of its Third-Party Fact-Checking programme to 10 additional African countries, which now join Kenya, Nigeria, South Africa, Cameroon and Senegal in the project,
In partnership with Agence France-Presse (AFP), the France 24 Observers, Pesa Check and Dubawa, this programme forms part of its work in helping assess the accuracy and quality of news people find on Facebook, whilst reducing the spread of misinformation on its platform.
Working with a network of fact-checking organizations, certified by the non-partisan International Fact-Checking Network, third-party fact-checking will now be available in Ethiopia, Zambia, Somalia and Burkina Faso through AFP, Uganda and Tanzania through both Pesa Check and AFP, Democratic Republic of Congo and Cote d’Ivoire through the France 24 Observers and AFP, Guinea Conakry through the France 24 Observers, and Ghana through Dubawa.
Feedback from the Facebook community is one of many signals Facebook uses to raise potentially false stories to fact-checkers for review. Local articles will be fact-checked alongside the verification of photos and videos. If one of our fact-checking partners identifies a story as false, Facebook will show it lower in News Feed, significantly reducing its distribution.
Kojo Boakye, Facebook Head of Public Policy, Africa, said: “The expansion of third-party fact-checking to now cover 15 countries in a little over a year shows firsthand our commitment and dedication to the continent, alongside our recent local language expansion as part of this programme. Taking steps to help tackle false news on Facebook is a responsibility we take seriously, we know misinformation is a problem, and these are important steps in continuing to address this issue. We know that third-party fact-checking alone is not the solution, it is one of many initiatives and programmes we are investing in to help to improve the quality of information people see on Facebook. While we’ve made great progress, we will keep investing to ensure Facebook remains a place for all ideas, but not for the spread of false news.”
When third-party fact-checkers fact-check a news story, Facebook will show these in Related Articles immediately below the story in News Feed. Page Admins and people on Facebook will also receive notifications if they try to share a story or have shared one in the past that’s been determined to be false, empowering people to decide for themselves what to read, trust, and share.
Providing fact-checking in English and French across eight countries, Phil Chetwynd, AFP Global News Director said: “AFP is delighted to be expanding its fact-checking project with Facebook. We are known for the high quality of our journalism from across Africa and we will be leveraging our unparalleled network of bureaus and journalists on the continent to combat misinformation.”
Eric Mugendi, Managing Editor from Pesa Check who will provide fact-checking services in Swahili and English added: “Social networks like Facebook haven’t just changed how Africans consume the news. Social media is often the primary access to digital content or the ‘Internet’ for many Africans. They shape our perceptions of the world, our public discourse, and how we interact with public figures. This project helps us dramatically expand our fact-checking to debunk claims that could otherwise cause real-world harm. The project helps us respond more quickly and directly. We’re seeing real positive results in our interactions with both publishers and the public itself. The project also helps our fact-checks reach a far larger audience than we would otherwise. This has helped us better understand the information vacuum and other viral dynamics that drive the spread of false information in Africa. Our growing impact is a small but tangible contribution to better informed societies in Africa.”
Caroline Anipah, Programme Officer, Dubawa (Ghana) said: “Dubawa is excited to be in Ghana where the misinformation and disinformation have become widespread as a result of technological advancement and increasing internet penetration. Dubawa intends to raise the quality of information available to the public with the ultimate aim of curbing the spread of misinformation and disinformation and promoting good governance and accountability.”
Derek Thomson, editor-in-chief of the France 24 Observers, said: “Our African users are constantly sending us questionable images and messages they’ve received via social media, asking us ‘Is this true? Can you check it?’ It’s our responsibility as fact-checking journalists to verify the information that’s circulating, and get the truth back out there. Participating in the Facebook programme helps ensure that our fact-checks are reaching the people who shared the false news in the first place.”