Augmenting Human Intelligence with AI
AI will be the leading driver for business competitiveness in the 20s
“In 2020, we will see a shift towards Human + AI. This type of Augmented Intelligence will empower people in organizations to make better and faster decisions by utilizing the wealth of knowledge from other team members and experts within organizations. Rather than taking in and retaining all information as equal, true AI will begin to mirror the way the human brain works – digging out what is important and forgetting less meaningful data. Real learning is based on recognizing when something you thought you knew has become obsolete and in 2020, the most advanced AIs will distinguish themselves through what they learn to forget, rather than simply what they were taught.”
- Oliver Muhr, CEO, Starmind
INTRODUCTION:
One of the most straightforward ways to think about artificial intelligence is to define it as a machine’s ability to understand or perform in a way that would normally need human intelligence.
A lot of what we see called AI is closer to automation. Automation is based on input and response: an input of X equals a response of Y. With the growing complexity of algorithms, the calculations undertaken to decide how to respond to a given input can be extremely complicated, meaning automated responses created in this way can give the impression of intelligence. But in reality, they are predetermined.
AI NEEDS TO BE MORE HUMAN — A LOOK AT NEURAL NETWORKS
We have greater access to information than ever before, but much of it is siloed or irrelevant. The beauty of the human brain is that it can strategically filter through large data and make sense of the chaos. Outdated or unused data is eliminated, preventing generalizations and making space for new intel.
The brain, however, processes, retrieves and stores knowledge very differently to a machine.
For example, a computer might process thousands of images of an animal to determine if it’s a cat or a dog. But a human can look at a cat, understand the core principles of it and forever understand what a cat is.
“True intelligence is not related to big data; it's related to the small, but correct, data.”
– Marc Vontobel, Founder and CTO, Starmind
The key for AI to function effectively is in creating a neural network that can process and learn to strategically forget data while keeping the concepts stored, just like a human, versus overwriting all the information it has acquired.
Artificial intelligence that constantly reevaluates previously learned information in the same way the human brain does, will help AI intelligently identify the most relevant data and use that in its decision-making process.This human-inspired AI can then apply insights to new situations in real time, with minimal computational power.
USING AI CAN MAKE PEOPLE MORE INTELLIGENT
Innovation in AI has fueled concern that people’s jobs will become redundant or worse, pose an existential threat.
McKinsey estimates that AI will lift productivity and economic growth which will see people switching occupations or upgrading skills.
Yes, this means that the way people work will change but it doesn’t mean AI will replace people’s jobs. Just as AI needs human input, using AI can enhance people’s intelligence and help them gain new skills. In a small company, this doesn’t cause an issue as you can find an expert within your team to help solve your problem. But for businesses or communities made up of thousands of people, it can be a big productivity drain and barrier for development.
While AI is unlikely to ever reach the human level, advanced artificial intelligence systems are starting to get better at adapting to unknown scenarios and functioning in ways that are closer to the human brain.
AI can help tap into your organizations rich intelligence by autonomously connecting employees and granting access to answers, expertise and support when they need it. Human knowledge will be paramount but AI can democratise it, so all individuals have the opportunity to learn.
Transforming how large enterprises work in the future.
Today, software-as-a-service (SaaS) tools have transformed how enterprises operate from internal collaboration through to sales or tech development. Artificial intelligence will define the next generation of SaaS software, allowing organizations to not just connect employees to each other or their software, but help them deeply understand and share the skills and knowledge they possess.
Onboarding, particularly at large enterprises, has meanwhile become a huge drain on organizations.
Attrition at some of the world's largest organizations stands at 15-20%.
By helping new joiners get up to speed quickly and giving them greater autonomy to find the knowledge they need, artificial intelligence will be crucial to reducing the vast expenses currently lost on onboarding.
Alongside this generational shift, digital-savvy millennials and Gen Zs are becoming the dominant force in the workplace. For these workers, support from AI will become a natural part of their workplace activity. Not only will it support these workers, helping them learn new skills and share their own like no generation before, but the companies that adopt smart use of AI will have a greater chance of impressing and retaining these workers for much longer.
Much like effective digital transformation was central to the success of business in the 00s and 10s, AI will be the leading competitive edge in the 20s.
Offsetting the risks of information overload and improving efficiency.
The data-boom and proliferation of powerful workplace software means we have greater access to information than ever before yet 80% of a business's knowledge remains undocumented — it's recorded not in a Google Doc or a Slack channel — but exists in an employee's mind. Organizations and solutions which can untap this knowledge can drastically improve efficiency.
In the same way that collaboration tools give employees transparent access to information and give them the autonomy to search for documents or previous discussions to find information they need, businesses going forward will need tools that let individuals find and share skills and knowledge.
Artificial intelligence will be central to this new era of driving business productivity. Ironically, it’s artificial intelligence which is best placed to unlock these human skills and usher in a new era of people-powered, creative and intelligent problem solving.
AI’s potential limitations
Concerns over AI range between how it could make jobs in almost every sector obsolete, to existential fears about the threat a super intelligent, self-learning machine could pose to humanity. For every stakeholder in artificial intelligence — from the programmer to the end user — it’s important to remain focused on using this powerful technology to support humans, not replace them.
AI can be designed to empower people to share their skills and knowledge. If you think about an organization or a community, the scope of human intelligence is vast. You may have hundreds of thousands of human brains, all with different perspectives, experiences and understanding. Unlocking this insight with AI could enhance people’s intelligence and fuel their careers. Teams can access answers and support when they need it (and pick up new skills of their own in the process).
For business leaders, using AI has clear positive knock-on effects from boosted productivity and efficiency, to greater workplace happiness and employee retention.
The risk in coming years is that businesses attempt to use AI negatively — instead of nurturing human knowledge and skills — it could be deployed to identify poor performance. If enterprises use AI to undermine their staff and make them feel vulnerable after a bad day or week, trust will evaporate. When considering how to use AI (or develop AI) all stakeholders should bear in mind that it’s much harder to win trust back after it’s been lost, than to positively maintain and build it.
Starmind AI at work
What’s clear is that organizations need to be increasingly dynamic to grow and retain the necessary intelligence and skills in their workforce to stay ahead of the game. The problem is, organizations are complex, so understanding exactly which skills lie where—and where the gaps are—can be a challenge.
Starmind’s technology helps organizations unlock this knowledge to benefit the organization as well as the employee.
USE CASE 1 – Accessing Undocumented Knowledge.
Starmind gives employees access to the intelligence and expertise they need to excel in their job and progress their careers. Crowdsourced company intelligence empowers the organization to get jobs done better, faster.
Example Pain Points:
- Slow and unproductive onboarding because HR needs to answer the same new employee questions over and over again
- Many experienced employees are leaving companies and with them a lot of undocumented / tacit knowledge
- Large product launches usually bring dozens and more questions across many departments (support, sales, pre-sales, customer success teams etc.)
Example Proof Points:
- Solving problems takes on average less than 2 hours
- HR workload reduction: Repetitive questions are answered immediately and 53% of new questions within 2h
- Sales onboarding efficiency gains and improved turn-time on complex RFPs due to access to information and quick expert identification
- Sales/Customer Support benefit from uploading questions & answers about a new product launch - increases speed of product capabilities education, reduces support tickets, increases higher customer satisfaction by getting answers faster, and saves on average $200 per ticket.
USE CASE 2 – Identifying expert intelligence
Starmind enables the identification of subject matter experts organization-wide that helps to unlock the potential of an entire enterprise and improves accuracy of information and faster turn times to answers.
Example Pain points:
- Longer than necessary projects because other departments ran in parallel, duplicating efforts and lack of cross communication
- Stalled innovation because cross-functional experts from different backgrounds (Engineering, Biology, Chemistry, etc.) are unaware of others’ roles and expertise because they work in different departments or locations
Example Proof points:
- R&D innovates faster and improves production time which reduces time-to-market. Anonymity in raising questions provides a protected environment for scientists to ask questions in their field of expertise
USE CASE 3: Develop Talent Intelligence
Starmind utilizes the power of AI + human interaction to generate live and company-relevant skill profiles that are the foundation for upskilling, re-skilling and workforce planning, With 200+ powerful connectors, our platform can ingest, learn from and continuously update employee’s skill profiles
Example Pain point:
- Hard to capture and quickly outdated skill profiles as they were manually generated or initially predefined based on role of the individual vs an understanding of all levels of the employees expertise. There is no or very little company specific learning involved and it does not reflect how skills evolve.
Example Proof points:
- Starmind creates a unique neural language and intelligence model for each organization and uses it to build specific skill profiles for each employee for HR and Managers to view at any time. The information is presented in a visual way that helps you quickly recognize the strengths and development areas of the team and/or the individual.. Starmind's AI, continuously learns new topics and clusters that evolve when new data points are added.
At Starmind rather than attempt to match the human brain in raw processing power, we are attempting to mimic the ways in which it learns. One example of this is teaching our AI to forget. It may sound counterintuitive, but one of the things that makes the brain so incredible is how it is able to rapidly re-learn and replace knowledge, forgetting obsolete knowledge is essential for it to learn.
Our patented artificial intelligence is constantly reevaluating previously learned information in the same way the human brain does. Rather than using huge amounts of old and useless data, it intelligently identifies the most relevant information and uses that in its decision-making process. Advances in AI may follow this model moving forward — it’s not simply about who can leverage the greatest amount of data, but how those AIs are using that data effectively.
Conclusion:
Moving forward there will be a greater focus on technologies that unlock the undocumented knowledge within organizations. This is the knowledge that isn’t saved, it exists in a team member’s brain; it’s their creative impulses, critical thinking, deeply held skills and expertise. This represents a vast, untapped resource globally.
Starting in 2020, AI technology tools will be increasingly important in releasing the potential of this knowledge as it becomes a differentiator for successful businesses.
With Gartner estimating organizations that implement AI could save 6.2 billion hours worth of productive work, AI’s new frontier will be human-powered knowledge networks.
Those developing (or using AI) will do well to focus less on how much or how fast an algorithm can learn, but instead spend more time on figuring out how AI can better replicate how the brain works. This will help pave the way for humans and technology to work together, not against each other.
To learn more about Starmind or to speak to someone regarding their Neural Know-How Network, go to starmind.ai
