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The Potential And Limitations Of Artificial Intelligence

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Everyone is excited about artificial intelligence. Great strides have been made in the technology and in the technique of machine learning. However, at this early stage in its development, we may need to curb our enthusiasm somewhat.

Already the value of AI can be seen in a wide range of trades including marketing and sales, business operation, insurance, banking and finance, and more. In short, it is an ideal way to perform a wide range of business activities from managing human capital and analyzing people’s performance through recruitment and more. Its potential runs through the thread of the entire business Eco structure. It is more than apparent already that the value of AI to the entire economy can be worth trillions of dollars.

Sometimes we may forget that AI is still an act in progress. Due to its infancy, there are still limitations to the technology that must be overcome before we are indeed in the brave new world of AI.

In a recent podcast published by the McKinsey Global Institute, a firm that analyzes the global economy, Michael Chui, chairman of the company and James Manyika, director, discussed what the limitations are on AI and what is being done to alleviate them.

Factors That Limit The Potential Of AI

Manyika noted that the limitations of AI are “purely technical.” He identified them as how to explain what the algorithm is doing? Why is it making the choices, outcomes and forecasts that it does? Then there are practical limitations involving the data as well as its use.

He explained that in the process of learning, we are giving computers data to not only program them, but also train them. “We’re teaching them,” he said. They are trained by providing them labeled data. Teaching a machine to identify objects in a photograph or to acknowledge a variance in a data stream that may indicate that a machine is going to breakdown is performed by feeding them a lot of labeled data that indicates that in this batch of data the machine is about to break and in that collection of data the machine is not about to break and the computer figures out if a machine is about to break.

Chui identified five limitations to AI that must be overcome. He explained that now humans are labeling the data. For example, people are going through photos of traffic and tracing out the cars and the lane markers to create labeled data that self-driving cars can use to create the algorithm needed to drive the cars.

Manyika noted that he knows of students who go to a public library to label art so that algorithms can be created that the computer uses to make forecasts. For example, in the United Kingdom, groups of people are identifying photos of different breeds of dogs, using labeled data that is used to create algorithms so that the computer can identify the data and know what it is.

This process is being used for medical purposes, he pointed out. People are labeling photographs of different types of tumors so that when a computer scans them, it can understand what a tumor is and what kind of tumor it is.

The problem is that an excessive amount of data is needed to teach the computer. The challenge is to create a way for the computer to go through the labeled data quicker.

Tools that are now being used to do that include generative adversarial networks (GAN). The tools use two networks — one generates the right things and the other distinguishes whether the computer is generating the right thing. The two networks compete against each other to permit the computer to do the right thing. This technique allows a computer to generate art in the style of a particular artist or generate architecture in the style of other things that have been observed.

Manyika pointed out people are currently experimenting with other techniques of machine learning. For example, he said that researchers at Microsoft Research Lab are developing in stream labeling, a process that labels the data through use. In other words, the computer is trying to interpret the data based on how it is being used. Although in stream labeling has been around for a while, it has recently made major strides. Still, according to Manyika, labeling data is a limitation that needs more development.

Another limitation to AI is not enough data. To combat the problem, companies that develop AI are acquiring data over multiple years. To try and cut down in the amount of time to gather data, companies are turning to simulated environments. Creating a simulated environment within a computer allows you to run more trials so that the computer can learn a lot more things quicker.

Then there is the problem of explaining why the computer decided what it did. Known as explainability, the issue deals with regulations and regulators who may investigate an algorithm’s decision. For example, if someone has been let out of jail on bond and someone else wasn’t, someone is going to want to know why. One could try to explain the decision, but it certainly will be difficult.

Chui explained that there is a technique being developed that can provide the explanation. Called LIME, which stands for locally interpretable model-agnostic explanation, it involves looking at parts of a model and inputs and seeing whether that alters the outcome. For example, if you are looking at a photo and trying to determine if the item in the photograph is a pickup truck or a car, then if the windscreen of the truck or the back of the car is changed, then does either one of those changes make a difference. That shows that the model is focusing on the back of the car or the windscreen of the truck to make a decision. What’s happening is that there are experiments being done on the model to determine what makes a difference.

Finally, biased data is also a limitation on AI. If the data going into the computer is biased, then the outcome is also biased. For example, we know that some communities are subject to more police presence than other communities. If the computer is to determine whether a high number of police in a community limits crime and the data comes from the neighborhood with heavy police presence and a neighborhood with little if any police presence, then the computer’s decision is based on more data from the neighborhood with police and no if any data from the neighborhood that do not have police. The oversampled neighborhood can cause a skewed conclusion. So reliance on AI may result in a reliance on inherent bias in the data. The challenge, therefore, is to figure out a way to “de-bias” the data.

So, as we can see the potential of AI, we also have to recognize its limitations. Don’t fret; AI researchers are working feverishly on the problems. Some things that were considered limitations on AI a few years ago are not today because of its quick development. That is why you need to constantly check with AI researchers what is possible today.

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Teaching Styles: Guide on the Side or Sage on the Stage?

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In the early 90’s California teachers were getting released in record numbers. There was a huge budget crisis, districts were raising class sizes and eliminating classrooms, which meant many of us had to go. I was a second year teacher, untenured. I received my goodbye notice in March then set out scrambling to find another position.

I found myself interviewing in the growing community of Moreno Valley. I felt I was ready for anything, but I’ll never forget the interviewer asking my about my style of teaching. He asked, “Would you consider yourself a Sage on the Stage or a Guide on the Side?”

What a great question. Simply asking the question implies so much. If I say that I am a Sage on the Stage, immediately I might be considered a micromanager. A power hungry control freak of a teacher who needs his/her students to act only on command. Or even worse, I might be seen as a showoff whose main goal in teaching is to hear ones’ own voice.

As I sat in the interview room, it seemed the more politically correct answer would be the Guide on the Side. “Guide” doesn’t seem like such a loaded word as “Sage”. A guide leads the way. A guide points out facts. Guides know what pitfalls to avoid.

I had to make a snap answer. It’s been almost two decades, and I still think about my response. I expected that in time, I would make revisions to my answer. Surprisingly, I feel still feel good about the response I gave.

Basically, I believe that there are times when a teacher needs to be the Sage on the Stage and times when the teacher needs to get out of the way and be a guide on the side. Additionally, I’ve seen very effective teachers who can work a class, create amazing discussions, and help students construct learning all from the front of the class. By contrast, I’ve seen other teachers who spend very little time in front of a class, choosing to do most of their teaching in groups. Therefore, the situation and the personality of the teacher play a great role in the debate: Sage on the Stage or Guide on the Side.

Reflecting on the question “Sage” or “Guide” is not a bad idea. My philosophy in teaching, as well as life, has always been balance and moderation. There have been times when I’ve been stuck in the Sage or Guide roll for longer than is necessary. Just asking yourself the question might lead to some meaningful soul searching and deeper understanding about yourself as a person and a teacher.

The Merits and Demerits of the Sage on the Stage

There are definite merits to the Sage on the Stage approach. The teacher on his/her stage, managing the flow of information is definitely faster than the Guide on the Side. I’ve tried to incorporate “guide on the side” strategies for my grammar lessons, but I’ve found that direct instruction works best when introducing initial concepts. I may use “guide” strategies to aid mastery of the information. However, there are dozens of grammar and punctuation skills the students are required to learn in ten months which does not lend itself to the Guide on the Side philosophy.

This benefit is also the biggest argument against the Sage approach. As more and more demands are heaped upon teachers, it is easier to get through the curriculum with this method. However, besides being exhausting for the teacher to be on the stage all day, students require time to digest and process information. Sage techniques such as lecture and group discussion tend to favor the quick thinkers. These students do most of the critical thinking for the class. Consequently, the majority of the class misses out on this important skill.

The Merits and Demerits of the Guide on the Side

I recently began a sixth grade unit on the Hebrew’s exodus from Egypt like this:

Imaging that you were a guest in someone’s house. After a few weeks, you realized that you were doing all the chores in the house, your mom was cooking all of the meals, and your dad began to pay all of the bills. You were once a guest in this house. Now, what have you become?

The students had to read the material from their social studies books and explain how the Hebrews were like your family in the story. The connections they found were excellent. The follow up discussion continued to bear fruit as one group after another pointed out new ways to look at the analogy. I was a guide on the side, interjecting hints along the way.

The follow up to this was that the students had to create the second part of my “guest” analogy. They read about Moses and the Exodus and had to create an analogy about how they were able to move out of the house where they had become slaves.

The lesson was time consuming, but very effective. As effective as it was, I noticed that there were still things that I needed to teach the students directly. Many students, having no background knowledge on the topic, needed me to put this time in history into context. Once again, I was back to being the Sage on the Stage.

Final Thoughts

The moral of this story is that the art of teaching is knowing when to be the “guide” and when to be the “sage”. Once again I return to my original point: Simply asking yourself the question “What Kind of Teacher Am I?” is enough to help make you a better teacher. Being ever mindful of the balance between the two provides the opportunity for the self-reflection we all need.

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Greatest Ever Barcelona XI

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Like many of the best teams in the world, its almost impossible to have just 1 team as a greatest XI. Barcelona arguably have had the biggest turnover of superstars to have played for the club. You have a who’s who of football to have turned out for the club. I could quite easily go for 3 teams for this great club, but I have settled for 2 teams.

Goal Keeper

Like most attacking sides, they have not had the very best goal keepers to have kept goal for them, so I have gone for Andoni Zubizaretta. He is Spain’s most capped player with 126 caps and was a very good goalkeeper.

Right full back

I have gone for Albert Ferrer, who was part of the first “dream team”. He was a very good defender as well as being excellent in going forward.

Left full back

I have gone for another member of the so called dream team, Sergi Barjuan. He was very identical in play to Ferrer as they were both quick, great on the ball and he could defend very competently.

Central defenders

I have gone for Miguel Nadal and Carlos Puyol. Both excellent players and whilst Nadal was known as “the beast”, he was very good on the ball. Puyol always gives his all in every game that I have seen him play.

Midfield

I have gone for a 4-man midfield comprising of 4 all-time greats of the game in Michael Laudrup, Johan Cruyff, Luiz Suarez and Laslo Kubala. Michael Laudrup was a wizard with the ball and perhaps did not get the world renown that his talents deserved, partly to do with the fact that he was Danish. Cruyff is a living legend and his reputation goes before him. Suarez is arguably the greatest ever talent to come out of Spain whilst Kubala was voted Barcelona’s greatest ever player.

Forwards

I have gone for Diego Maradona and Romario. I have read too many times that Maradona was not successful at Barcelona, but that’s comparing him to himself and not by any other player’s standards. I have seen matches that he was involved in at Barcelona and he was breathtaking at times. Romario was just a born goal scorer.

Team 2

Goal keeper

I have gone for Francisco Platko, the Hungarian, whom, I have to admit I have never seen play but he is reported to be very good and I did not that many options.

Defenders

This time I have gone for 3 defenders and they are Jose Ramon Alesanco who captained the club for a long period of time and was a very good defender and leader, Ronald Koeman, okay, he was not a very good defender in terms of actual defending and maybe he would just pip a tortoise in a 100 metre sprint, but he could pass the ball like no other and had a shot on him to die for. He also scored 1 of the most memorable goals in the club’s history, when he scored the winning goal at Wembley, against Sampdoria for Barcelona to win their first ever European Cup. The third defender is Migueli who played for Barcelona from 1973 to 1989.

Midfield

I have gone for a 5-man midfield comprising another array of wonderful footballers. The first is Luis Figo, whom I felt played his best football at Barcelona and he was absolutely terrific. Whilst teammate, Rivaldo, was getting all the plaudits, Figo. I felt was the best player. The second midfielder was a mainstay of Cruyff’s dream team and that was Pep Guardiola, who was one of the best playmakers, I have ever seen. Injuries blighted a bit what should have been a superlative career. Ronaldinho is my third midfielder as he is truly majestic and surely, even at this stage in his career, already an all-time great. The next is his Brazilian compatriot, Rivaldo who will always be remembered fondly at the Nou camp for scoring, perhaps, the greatest hat-trick ever, against Valencia, which enabled Barcelona to qualify for the champion’s league, on the last day of that particular season 2000/2001. Last but not least, I have chosen volatile but brilliant Bulgarian attacking midfielder/forward, Hristo Stoichkov. Stoichkov had a seemingly love-hate relationship with equally brilliant and equally volatile Romario. One minute they are hugging each other for setting up the other for another brilliant goal and the next minute they are sniping at each other because one of feels that the other did not pass the ball to him.

Strikers

I have gone for the absolutely brilliant Brazilian Ronaldo and Sandor Koscis.

I know I said I will only pick 2 teams but way too many players that I like have not been picked because just too many greats played for Barcelona, so I have managed to squeeze in a third team

Goalkeeper

For Goalkeeper, I have gone for Antoni Ramalletts who played for Barcelona in the 40s to 60s and won the best goalkeeper award for 5 consecutive seasons in the 50s

Defenders

I have gone for Abelardo Fernandez, a very capable defender who always gave his best, Juan Asensi who was also a very good defender for both Barcelona and Spain and Eric Gensana.

Midfield

I have gone for Bernd Schuster, the current manager, who was a brilliant midfielder and should have won far more caps for West Germany, if not for his bad relationship with the West German FA. Luis Enrique, one of my favourite players with his all-action style and loads of goals to boot. For a midfielder, he scored a fair amount of goals. Allan Simonsen, the brilliant Dane, who was European footballer of the year in 1977. Johan Neeskens, the current assistant manager, who was a wonderful midfield player.

Strikers

I have gone for a 3-prong attack and they are Paulino Alcantara who though I have never seen play scored 357 goals in 357 matches, now that is impressive. Josep Samiter who scored 326 goals for Barcelona and Hans Krankl just edging out Samuel Etoo and Patrick Kluivert.

Some of the players that I have not mentioned include the present crop of players like Rafa Marquez, Thuram, Xavi, Deco, Messi, Zambrotta and past greats and good like Hagi, Prosinescki, Laurent Blanc, Gica Popescu, Carles Rexach, Jari Littmanen, both De Boers, Cocu, Laarsson, Mark Hughes, Lineker, Beguiristain, Goikoietxea, Edgar Davids, Riqueleme and Sorin amongst others.

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5 Simple Steps to Be a Media Star

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This series of articles are focused on how to become known as an expert. Today we will focus on how to gain media attention.

Dale Carnegie said in his famous book – How To Win Friends and Influence People, “babies cry for and grown men die for”. We all want attention and recognition. We seek media attention to get our name splashed in newspapers, radio and TV. Not only is it something we personally want but it is also a great strategy to gain expert status and get clients.

I have been written up in print, interviewed on radio and TV. Did you know one appearance on TV can catapult you into fame and launch your career into the stratosphere? Fawn Germer, who I recently hear speak, was featured on Oprah. She has leveraged it to the hilt. We all know what can happen if you are seen on The Oprah Show. Businesses become hugely successful and a million books are sold! Dr. Phil and Dr. OZ started as guests on The Oprah Show. Now they have their own shows.

So how do you get attention of the media?

Here are 5 simple strategies:

  1. Find an angle that will appeal to the media: It is quite easy to look up what current stories are already being covered in the media. Just find an angle to latch on to the story. It is not enough to say that you are a chiropractor or a massage therapist. What is new, unique or newsworthy about your profession?
  2. Prepare you story: Once you know the angle, create a pitch that is easy for you to communicate. Human interest stories are featured all the time. Pick a struggle and how you or a client overcame that struggle.
  3. Get a list of reporters: Today it is easier to find reporters on the internet. Social media has made reporters and journalists much more accessible. Pick the target market you want to focus on and find the reporters who cover such stories.
  4. Call or email them: Depending on the information you have and how timely it is, you can just pick up the phone and call the reporter. Make sure you are aware of simple protocols. TV, radio and print media – all have different strategies in collecting and sharing information. Pay attention to when and how you should approach the media.
  5. Build a relationship: I consistently write comments to the reporters. You will be amazed how many of them will reply back. Make it a habit to communicate with them so you can be recognized. Today the media is required to build a following and be in touch with their audience.

These simple and effective strategies will help you start moving towards being a media star.

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