Winning factors in a Multi sided Platform Model ..

Multi sided platform models are catching up these days.  

 

Click here for the Sloan Management Review link, Leslie Brokaw, May '14

1. Aim for volume

2. Aim for Economies of scale

3. MSPs are a chicken and egg proposition

4. Answering strategy questions are  vital to success like

•    how many sides will  be part of platform
•    what should the platform design be
•    what is the pricing / is it free to one side ?
•    what governance rules are need to ensure fairp[lay among participants ?
  

5S quiz, EPGDM sem 4, Jan 2021 batch.

 Pl click on this link and answer this quiz.  Click here..

For the answers click here ..

George.

Building and Managing AI powered organizations . .

Most large organizations talk big about their AI initiatives,  but fail in managing these initiatives well. We know of small organisations that want to implement AI, but find the AI initiatives are too expensive and hence is beyond the reach of the common industry or organisation. It is indeed a fact any organisation would need AI intervention only if it becomes unyieldy in terms of operations.

While reading an HBR July 2019 article in this regard Building the AI powered Organisation, click here, the authors Tim Fountaine, Brian and Tamim Saleh, have tried to understand why AI projects are generally not as successful as other industrial projects.  

 

The AI area as the cutting edge technology breakthrough that will influence how cognitive work gets done in future, will contribute about $ 13 trillion this decade from 2021 to 2030. The authors while working with thousands of executives in the cutting edge of technology were frank enough to admit that only 8% of them are engaged in research and applications in the AI area. 

The following three points the authors feel can help organizations running AI projects turn successful 

1. Inter-disciplinary approach : Instead of a siloed approach, promoting inter disciplinary collaboration 

2. Data driven decision making mindset : From experienced and leader based decision making to data driven decision making mindset and 

3. Agile, experimental and adaptable work environment : From a rigid and risk averse setup, moving to an agile, experimental and adaptable working environment 

The authors of the paper also feel that for successful AI launches in organizations, attention should be focused in the following areas.

1. Explaining to the stakeholders as to why the AI project is necessary 

2. Anticipating unique barriers to change, workers fearing losing jobs 

3. Budgeting equally for integration and adoption as spent on technology acquisition  

4. Balancing feasibility, time investment and value - investing in projects that are tough and time consuming initially can sabotage project success 

AI projects like any other projects need effective and refined project management skills to be successful in the long run. In the initial stages small AI projects that are easy to implement should be taken up before attempting ambitous ones.

 

Daniel Newman writing for Forbes in Feb 2020 (click here) stresses on why one needs to focus on the positives of AI adoption than on the negatives and job losses resulting from AI adoption.  

 

As we know, 

• promoting automation, 
• augmenting human based decision making and 
• enabling AI promoted improved awareness of the environmental context in which we live        are three areas where AI apps can benefit humans. 

Usually we find it hard to do repetitive tasks like washing. Using the washing machine eliminates the hard work of washing clothes for humans. The whole washing cycle is programmed in the washing machine making it easier to finish the washing without bothering humans. The advanced GE-Haier washing machine helps by telling the amount of detergent and the length of the washing cycle, all the while using optimal quantity of water. Earlier these were human based decision making processes, now replaced by the AI fuzzy logic capabilities of the washing machine. 

Future applications of AI in our normal lives will find AI assisting in helping the workers in engineering construction site or in potential hazardous environment being warned by sensors of the inherent danger, democratising healthcare making it possible for patients in remote areas have access to high quality medical care year round,  helping the aged age in their own homes safely and being reminded by alarms and sensors when to take medicines etc.

Humans while not allowing AI to have the upper hand, should incorporate AI into their daily lives that will make our daily living and business tasks more enjoyable, safe and interesting.

 

George (Image courtesy Forbes)

Impact of AI experiment on Chinese students . .

Preparing tor the management classes that are coming up from Monday 4 Jan '21, the new topic of Management of Artificial Intelligence and its varied impacts, besides being advanced is at the same time challenging too for classroom discussions. 

Placing headbands on school children's heads and monitoring their concentration levels with 3 sensors,  one on the forehead and 2 others behind the ears to help monitor concen6and attention spans is in itself a draconian exercise. Why ?

 

Wall Street Journal in October '19 came out with this very controversial video. It shows Chinese school students with headbands attending school.  Click here to watch the video ..

Watching the video, educators around the world are besides shocked, very alarmed at how Chinese school students are being made the items of experimentation. What will happen if in future these students are adversely affected out of the experiment and develop adverse negative reactions and are unable to cope up with adolescence and adult hood peacefully ? Inside the class, the willingness to concentrate or not is personal. Having a machine through sensors individually monitor each student all the time in the class is no doubt, invading student privacy.

Some questions that arise in our mind are the following : 

• Do we really need such monitors to constantly keep track of activities ? 
• Will the improvement in productivity and performance be compensated by the deterioration of mental health ? 
• Will it result in a sort of phobia for machines and AI in children that could develop into mental health problems for future generations of children  ?
• Will it cultivate a slave mentality in children compromised at the altar of high academic grades ?

Variety is the spice of life. The inherent variety and diversity in class student performance adds flavor to school performance . If all students consistently give high academic achievements and performance,  where is humanity heading to ?

Is successful life solely dependent on one's academic grades ?

Will this experiment have any long term impact on mental health of the students or into the future into adolescence? Has any initial experiment been done to assess the long term impact of this experiment on students  ?

On the face of it, the study appears very wrongly oriented, planned and timed.  The world would be very interested (if and when China discloses it), in knowing the immediate positive and negative impact of this experiment on student population and on the future personality development of these students. 

George ..

How can Artificial Intelligence (AI) help business ?

Having read lots about the benefits of AI and how AI would transform humanity, I was very inquisitive to know in spite of all the hype around AI, have we started using AI in a big way. 

In Dec 2018, I was attending a one day program on AI at the Indian Institute of Management, Bangalore which had an afternoon session with IBM engineers. Towards the end of their demo, I asked the engineers what were the actual applications of AI by IBM in the present day world, at least in India. The engineer was frank enough and admitted that it was just chatbot applications. 

AI had not matured beyond that at least for the industry. Even after two years, I find other than Google in their Maps, Gmail, search apps, not much AI is available in public domain for people to start using and experience the benefits.

While going through the article AI for the real world by Prof. Davenport and Ronanki in Feb '18, HBR (click here), I was able to understand what were the business benefits of AI and in general what were the AI challenges that global organisations face. 

Why are organistions skeptical of implementing AI when there is so much hype around it, is a question that would naturally come to any manager or engineer working in the industry. 

An anagram IEPPIO is apt for this occasion as per primary research conducted by the HBR paper authors on 250 executives in 152 AI projects, gave the real challenge faced by AI in the real world. 

I - ntegration

E - xpensive

P - oor understanding

P - eople

I - nnovative technology and 

O - verhyped technologies

The world is yet to fully understand the cognitive ability of humans, how humans distinguish one decision from another and in spite of the best intentions, fails completely in this area.

Of course, the technologies are too expensive, which takes it out of the realm of ordinary startups and medium sized organisations. 

We are yet to fully understand the nuances of AI and its applications

We do not yet have the real human resources to support full deployment of AI across organisations

Even though we extrapolate saying what all the technologies can do, we have immaturely developed technologies, ie. over hyping it.

The over hype or over selling of the technology has created a sort of glass palaces in the minds of the public and they expect AI to change the world radically overnight, which is not possible.

Once we know the challenges faced by AI, it makes sense to understand how we can overcome it. 

Understanding the Business benefits of AI

• I mprove
  
• O ptimise internal systems
• F ree workers from monotoinous tasks to do creative work
• B etter understandiong of p[roducts and processes
• C reate new products
• O ptimise external processes like Marketing etc
• P ursue new markets
• C apture new knowledge to venture into new products and processes
• R educe headcount at organisations
  

The potential business benefits of AI is great as how we understand it, the benefits may again increase over time as we progressively understand more features of the AI system. 

All these benefits if exploited well can result in great commercial benefits, besides reducing the boredom and monotony experienced by employees at their workplace.

George..

Role play on Artificial Intelligence in the class

We all know of the very many ways in which Artificial Intelligence (AI) is playing a very important role in our daily lives.  From the very simple search on Google, to replying to our emails on Gmail, to translating docs from one of the popular languages on Google Translate to another language, to the use of Personal Assistants from Amazon, Google, Microsoft or Apple, the uses of AI are varied and colourful. 

One of the biggest challenges for an AI system is to collect enough training data to prepare the AI system to learn and help make correct future decisions. If we start on poor quality training data and low volumes of training data, the output also would be equally poor, incorrect and incompetent.

The availability of large volumes of high quality training data is gives organisation the early mover advantage. 

The entry of Google in the search domain decades back gives it so much of training data and strong algorithms that can help it get the right search output for your search inputs. It will be very difficult for a new search engine incumbent to beat Google in search at least for the next fifty years. 

Maybe a new SEARCH ENGINE player with a 

• radically different approach to AI effectiveness or 
• strong faster processors working on quantum computing or
• ultra fast communication protocol for the results from servers to customer desktops or
  
• an efficient, innovative and quick algorithm may be able to thwart Google.

The role play being designed in the class for students is to help them understand the importance of high quality training data for a high quality AI output. 

What are the different ways in which an organisation can try to collect large volumes of high quality training data in a short time ? (click here for interesting AI based case studies)

Can it collect this training data from 

• different functionally related areas, 
• geographically different areas 
• different set of customers
• equivalent product markets ??

Let us leave it to the ingenuity of the students to tell us from where to collect the training data to help the AI systems take the right decisions .. 

Ref : 1. Ajay Agrawal,Joshua Gans, and Avi Goldfarb, How to win with Machine Learning, HBR, Oct '20.

George..

Types of AI

Artificial Intelligence is growing these days and is attractinmg attention of scientists and managers from across the globe.

Referring to the article 7 types of Artificial Intelligence, in Forbes of June 2019 where the seven different types of AI classifications are briefly mentioned.

The basic classification of Artificial Intelligence is of two types based on the likeness to the human mind and the ability to analyse.

According to the classification of AI based on it's likeliness to the human mind, Reactive, Limited Memory, Theory of Mind and Self Aware AI are the different classifications.

1. Reactive AI machines are 

• limited in their applications.
• do not have memory based functionality
• no ability to learn from previously gained experiences
• can only respond to a limited set or combination of inputs
• cannot improve their operations

An example is IBM's famous chess playing Super Computer Deep Blue. 

2. Limited Memory AI is what we observe in chatbots, Personal Assistants like Amazon echo, Google Home, Microsoft Cortana and Apple Siri, all self-driving vehicles.

In addition to the capabilities of Reactive Machines, these AI machines can learn from historical data to make use in decision making. Image recognition that makes use of Machine Learning and Deep Learning is an example of this. 

Image Courtesy, Forbes.

3. Theory of Mind AI is futuristic and exist only as a concept or work-in-progress

A Theory of mind AI will be able to better understand the entities by being able to discern the needs, emotions, beliefs and thought processes of the entities it is interacting with.  Theory of Mind AI tries to understand humans better.

4. Self Aware AI is akin to the human brain with all it's rationalising and emotional capabilities.

Though it may takes decades or centuries to fully realise and understand this type of AI, it can change humanity for the better or consign it for doom or disaster. The potential for self-preservation of these AI machines, can take over or spell the end of humanity, which can be a great threat to the world.

The other three types of AI are 

• Artificial Narrow Intelligence which we see in all our current applications with learning capabilities and ability to perform repetitive tasks autonomously using human like capabilities. 
• Artificial General Intelligence is futuristic and is the ability of machines to learn, perceive, understand and function like human beings. They develop competencies across multiple capabilities and domains with reduced learning time to carry out tasks efficiently and accurately.
• Artificial Super Intelligence is the ultimate in AI development. Because of their multi faceted intelligence these machines will be better capable at doing all things better than humans because of their faster memory, data processing, analysis and decision making capabilities. These machines can also spell the doom of humanity, thus being a great risk. 

How can humanity make effective use of these different types of AI to help in growth of humanity and not its doom is a serious question facing human civilization now. Can we, if not control, at least co-exist with AGI or ASi to help humanity for the next millennia ?

George.