The author of article said that the usage of artificial intelligence tools requires the ability and skills of people to use them. Adding AI tools does not automatically increase performance if people who use them do not use the technology correctly. So far, there are no studies that would indicate what skills employees need to have to use tools based on artificial intelligence. Choudhury intends to conduct such research and point out the complementarity between human capital and machine learning.
Choudhury conducted a survey at the US patent office, where he proved that it does not matter which technology is applied. It was important whether a person has IT and engineering skills. Many companies spend huge amounts on introducing artificial intelligence and count on immediate improvement of efficiency and reduction of errors. In the vast majority, they are used by people without IT experience.
The article emphasises that companies must take into account the need to train employees because they risk the failure of their technology. Using these tools without knowledge only reduces productivity and increases errors. This does not mean that only IT specialists are fit for work. The current employees should be intensively trained.
In addition, in autumn, a more accurate study / experiment will be conducted with the participation of 1,000 people.
I have chosen the following article „ The Civic Benefits of Google Street View and Yelp”. Here is the link to the article https://hbswk.hbs.edu/item/the-civic-benefits-of-google-street-view-and-yelp.
The author states that the data which is being constantly generated in the world, have the potential to improve, develop and help in evaluating and understanding the real world better. Nowadays, there are the vast amounts of data so the knowledge how to use it becomes extremely important. A dataset may be used several times for many application. The following examples were presented in the paper: Google Street View and Yelp. The mentioned companies collected the data for their purpose but it can be used for other aims as well.
As you probably know, Google street View is a technology that provides panoramic views from positions along many streets in the world. In the reviewed research the images of New York streets obtained from Google Street View were also used to teach the computer to recognize some features like driveways, sidewalks and etc. Additionally, the dataset was labeled with income and the machine learning model was trained to associate between the mentioned features and the incomes. The solution may be applied in the cities where population surveys are conducted every several years in order to improve data assessment thus making their policy more flexible.
The second example which was presented in the research paper is Yelp. Yelp is a local-search service powered by crowd-sourced review forum mainly about restaurant. The dataset including reviews was used to find the restaurants which should be inspected. Searching a dirty restaurant was based on the analysis of specific word combinations in such a way that the model was trained to recognize the problematic restaurants.
In my opinion using the same datasets in multiple application may provide promising results opening new horizons in fundamental and practical data science. Certainly, there are some problems associated with this idea – machine learning is not a panacea, the models should be designed in accordance with the particular subject field it is going to be used in. Nevertheless, scientific literature provides numerous evidences of civic benefits in cases when a model is thoroughly planned and adjusted for use in specific area. Some people think that big data can solve every problem. In my point of view this statement is not completely truthful nowadays. However, proper gathering of big data allows to collect more information and it would let to solve more and more problems in the future. I think that there are more civic benefits than disadvantages of big data approach. Even if some part of people can lose their jobs due to the fact that company will not need them (for example person who carry out surveys in the future), they will still be able to find another job which is needed.
The article that interested me is "What Should Mark Zuckerberg Do?", Facebook's popularity has been falling for several years. But Zuckerberg is also the owner of Instagram and Tinder. and many other small projects. Unlike Facebook, Instagram popularity is growing rapidly. This year, the instagram has been recognized as one of the best investments in the world(was bought for 1 billion dollars. and its current price is about 100 billion dollars). But given the scandals around Zuckerberg , there is a possibility that his fate will befall Elon Musk. Already this year there were scandals, with the leakage of personal information of users from Facebook, as well. with the Facebook advertising algorithm that was used to send out fake news, and many more. Zuckerberg already spoke to the US Senate. I think in the near future, the management of Facebook will be revised.
I have chosen an article "Companies Love Big Data But Lack the Strategy To Use It Effectively"
Nowadays, all the larger companies collect an incredible amount of information. As the amount of information grows faster and faster, there is a problem with its use. The problem is that, in many cases, big data is not used well. Companies are better at collecting data–about their customers, about their products, about competitors than analyzing that data and designing strategy around it. There is also a fear of what we will do with so much data if the Internet of things continues to grow. Using such data and making business decisions on this basis will be one of the most important things for all relevant companies. It can also be useful in sport and medicine and change the life of each one of us.
“Health care is rife with examples like these—and such applications of big data will only expand over the coming years. I spend a lot of time thinking about questions like, How will artificial intelligence change the medical diagnostics industry? How will better data collection transform the ways in which we do clinical trials for new cancer drugs? It is both staggering and exciting to imagine how data and analytic capabilities will transform entire industries and it was thrilling to engage in these conversations with folks from such rich and diverse backgrounds.” Ariel Dora Stern
Data shared on community poratalch should be carefully protected. We are all aware of the fact that posted photos and information are used by people (criminals) for "bad" purposes. For sure, current facebook needs remodeling. Today, not everything can and must be free. However, you should officially give what and how much it costs, or how to earn it, so that users are conscious users!
I have chosen the article: https://hbswk.hbs.edu/item/is-apple-s-real-privacy-challenge-technology-innovation-itself
This article is very interesting indeed. Is it good that Apple wouldn' like to share the data with the bureau when it comes to the crime suspicion, but can share the data with third companies to earn more money? Where is the border of what is ok, and what is too far?
The additional fact to take into consideration that something has changed apparently. A few days ago Apple's CEO said:
I selected Why Artificial Intelligence Isn't a Sure Thing to Increase Productivity from: https://hbswk.hbs.edu/item/artificial-intelligence-tools-won-t-automatically-increase-productivity
The article is about the experiment comparing productivity of workers examining patent applications depending on their educational background. Students where divided into two groups, one was given a Boolean search tool and the other a sophisticated AI tool. Furthermore, halves of each group had access to an expert advise. The task was to examine patent application to check if it's really innovative and similar idea haven't existed before.
The experiment shown that no one succeed without an expert advise. Results of those who had an access to experts depended on their educational background and a tool used. Those with a Computer Science related degree did better with an AI tool while others were more effective with a Boolean search tool.
Of course the article is not scientific so it was expected but still experimetnal setup is lacking important details and the results sound manipulative. The article states that AI tool was accepting a whole document (paten application) as and input and providing related documents as an output. Considering such interface it seems unreasonable that any background in Computer Science was necessary to use such tool. If the results obtained by subjects using this tool was indeed worse then the tool itself should be examined. Maybe suggestions made by the tool were irrelevant and it may has nothing to the educational background of subjects.
I have chose "What Should Mark Zuckerberg Do?". The huge success of Facebook comes from the fact that it is widely available and free. People do not know the term TANSTAAFL (https://en.wikipedia.org/wiki/There_ain%27t_no_such_thing_as_a_free_lunch). That if something is available without charges, it must be earning something differently. In the case of Facebook, user is the product. They are selling information about their users. As long as the principles of such cooperation are clearly defined and understood by users, everything is fine. Worse, if large corporations such as Facebook violate our trust and try to maximize profits at our expense (https://en.wikipedia.org/wiki/Facebook-Cambridge_Analytica_data_scandal). In my opinion, Facebook should introduce paid subscriptions in exchange for more privacy.
I have chosen the article:Online Match-Making with Virtual Dates https://hbswk.hbs.edu/item/online-match-making-with-virtual-dates
There are many people who have found their other halves via the Internet. However, the current models used to connect people in pairs are very artificial, static and distant from real interpersonal interactions. Currently, dating sites are designed as if searching for love was a variation on online shopping. People spend too much time looking for a person with whom they can go for a coffee instead of getting to know people through conversation. They are often disappointed after their first meeting because someone has not turned out like they expected. Online dating allows for long-term formation of ideas about a partner that is not real because no social feedback is obtained, everything is a figment of one's imagination. People are searching using criteria, but they don’t include subtleties that only appear when you meet someone.
That's why researchers came up with the idea of virtual dates. If two portal users find a good match between themselves, the couple will meet on a 5-minute date by computer. The date is some sort of ice-breaker. Thanks to this, they can capture certain nuances such as reacting to certain words, behavior, etc. Virtual dates provide auditory and visual experiences, thanks to which people can interact with each other as if they were on a real date in a museum or gallery. They can share their views and opinions on a given topic. It is not dry conversation via the communicator, where they don’t know how to start a conversation.
Idea standing behind virtual dates can be used to develop applications that allow people with similar interests to form new friendships and relationships. There is also possibility to create applications for older people, which allow them to meet other people and not feel lonely.
I think that the idea of virtual meetings is very interesting and helps to overcome shyness when getting to know each other. It also helps to better assess our interest in the person. However, one should remember not to limit the search for love or friendship only to the Internet because virtual dates can’t substitute real experience of meeting someone face to face, no matter how real they can become.
Hi, It was very inspiring for me to read “Water, Energy and Transportation: Preparing for the Population Boom” (https://hbswk.hbs.edu/item/water-electricity-and-transportation-preparing-for-the-population-boom). I’ve been working in energy sector for 18 years, so this issue is double interesting for me, not also because of my private ecological interests. What we’re searching now, are holistic solutions for both public and private markets, in order to provide not only appropriate resources, but also their optimal configuration. This is a huge challenge for contemporary IT. This article presents a very good summary of those three powers usage. As for energy, there are two thoughts given to analyze and to inspire to do something with: our buildings are not energy efficiently prepared, and people are not saving energy (and not open to any change in this respect). In respect of water, I didn’t think before that it works like most of it is used for industrial purposes, only small percentage of that goes to our everyday usage. As for transportation, definitely this is a permanently growing problem, which can be solved with using respective IT solutions. A sustainable and affordable energy supply, a safe access to clean water and an efficient environmental protection: information and communication are together the issues to be taken into consideration. The industrial clients and public-sector customers expect urgently high-performance IT solutions which have an “superordinate” perspective approach enabling holistic solutions for all the problems mentioned in the article and other details, connected to them. Because the issues are fundamental to survive in many-years-forward perspective, I reccomend to think it over, but first to read this article. Have a nice evening :-)
The article presents the benefits of data generated by people around the world. The author in his publication focuses on the Google StreetView and Yelp applications.
Currently almost everyone has a smartphone with installed applications that generates huge amounts of data. This data can be used to improve the lives of people in the cities. Available opinions on given places allow you to choose, for example a restaurant that serves the best dishes in the city. Traffic monitoring allows you to choose the fastest route to your home or store bypassing congested streets and city authorities to improve communication by changing the traffic organization or by setting additional traffic lights. Good data usage can be beneficial for the city's development.
I've choosen "Two Decades Later, is the 'New Economy' Finally Here?" https://hbswk.hbs.edu/item/two-decades-later-is-the-new-economy-finally-here
The article is revisits question from an older one, 2000 "Whither the Information Economy?", which seems to be induced by 1982 "Information as a Resource".
Enthusiasm and pesimism intertwine in this article. Author notes that "New Economy" did not deliver "the promise of significantly greater productivity and growth through technology". On the other hand, notes the existence of "Exponential Organizations (ExOs)" - entities that grow in financial performance with exponential rate while maintaining employment on same levels. Other reviewed book conclude we witness the shift from physical economy "atoms/bricks" to information-based "clicks/bits".
I disagree the "New Economy" is something radically different and having potential of unbound growth. Of given examples of ExOs (Google, Netflix, Airbnb, Amazon) - only two have strong base - Amazon with its retail encompassing new and new areas, and Google that want to collect and process all the data it can. Airbnb (and also Uber) acts as a mediator between customers and suppliers, and both customers and suppliers can switch to other - better or cheaper - mediator without thinking twice. Netflix depends on goodwill of the movie studios, and can be strangled by them in no time. I think all this exponentiality observed is just temporary adjustment due to slightly better planning and operations in some cases, and result of shifting costs onto sub-contractors in other - not sustainable.
What really matters - agriculture, construction, textile, semiconductors, steel and plastics - it is all still bound by matter and energy input, and this will not change soon.
I have chisen an article "Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change". I was interested how to measure a gentrification for scientific purposes. The authors explain how data from yelp may be used to forecast changes in hose prices. They also analyse how openng a new store or cafe may change the local demographic. It is quite interesting study where we can see that correlation can help topredict something but we do not analyse the causation.
I am finding most interesting the article 'Companies Love Big Data But Lack the Strategy To Use It Effectively'. Author if the article is deliberating about different strategies and approaches of companies that are implementing big data technology in real world business cases. The problem is that, in many cases, big data is not used well. Companies are better at collecting data–about their customers, about their products, about competitors– than analyzing that data and designing strategy around it. Related articles
I’ve chosen an article: „Why Artificial Intelligence Isn't a Sure Thing to Increase Productivity” (https://hbswk.hbs.edu/item/artificial-intelligence-tools-won-t-automatically-increase-productivity).
The author of the article believes that the use of Artificial Intelligence does not have to increase the efficiency of human work. It depends on computer science experience of the employees. Even if the given tool will be a great tool, employees will be still less productive.
Choudhury claims that employees without computer science background should have extensive training to use machine learning tools efficiency. In connection with this conclusion he expands the area of his research and tries to find out whether these people will catch up and the productivity gap narrows.
In my point of view the selected statistical group is too homogeneous. Undoubtedly, such research is a good contribution to further study of the problem, which perhaps is not repetitive in another environment. I agree with Adam that the cause of the problem is in the tool itself rather than in its operator. If such tool will be used by people without computer science experience, it should be just well prepared. I think it does not depend on the user’s background.
I have chosen the following article: "10 Reasons Customers Might Resist Windows 8" from: https://hbswk.hbs.edu/item/10-reasons-customers-might-resist-windows-8
The article presents some reasons why people might resist Windows 8. It mainly consists of losing control over the system, difficulties with learning how to use it properly, and aversion to changes.
I could agree with them, but I got rid of the Microsoft's system before the appearance of windows 8, because I wanted to have more control over the system, so I have never had an opportunity to check how well the system worked. The only thing I know about Winodws 8 system is it has terrible and non-functional tiles. I tried Windows 8 at my university once and for me in, user interface was unfriendly and very confusing.
In fact, as we can say after almost 6 years, Windows 8 was not welcomed well. People found it strange and hard to work with. The next version – Windows 10 – returned to the old look, without all these files, with the big Start button in the left corner.
Moreover, this is not the only failure of the Microsoft - usage share of operating systems on mobile devices is less than 1%.
As we can say after reading described article, sometimes putting too much effort in changing the product may results in dismissal it by consumers.
I chose this article, https://hbswk.hbs.edu/item/the-business-of-free-software-enterprise-incentives-investment-and-motivation-in-the-open-source-community. One could say that hell has frozen. Once Microsoft considered free software, including Linux, to be the main threat to itself. Since then, a lot has changed and not only does the giant look much more favourably at free software. Microsoft recently joined the Open Innovation Network (OIN). OIN is an association of several companies and institutions (including Google, IBM, Novell, Philips, Red Hat, Sony and SUSE), whose task is to acquire and make available Linux patents in exchange for waiving claims against technologies used in Linux. After Microsoft's accession to the OIN, everyone will be able to use Microsoft's 60,000 software patents for free.
My last post did not appear here, I am posting again
"Learning Curve: Making the Most of Outsourcing" (https://hbswk.hbs.edu/item/learning-curve-making-the-most-of-outsourcing)
Outsourcing was falsely advertised as a way around on-the-job training, managing human resources and other "non-productive" costs associated with hiring people to do the job as employees. It turns out, that there are limits to what can be done with labor-as-commodity. It has been shown before, e.g. in the case of the Amazon Mechanical Turk (a massive crowdsourcing platform for HITs - Human Intelligence Tasks), that in some cases building expertise is indispensible. The above article is another argument in this discussion.
The articule I chose touch important topic: How data driven decision changing one industry over another. First not obvious is Sport: „New Zealand’s yacht designers and crew prepared for the 1995 Americas Cup with a radical, data-intensive experimental design.” Another example from this field: „German soccer team TSG Hoffenheim deploys analytics in scouting and player development.”
Naturaly the best place to use data driven decison is business, where objectivity is so important. The advantage of this sector are data itselfe. Companies are gatering all avaiable data, because with current technology it's cheap and process is well know. But it's not enough, rough data will not magically speak for them selfs. This is where some companies hit the wall, they don't have strategy how to use all valuable data, that could answered all the question.
Article mentions also new approche to creat multidisciplinary team called “people analytics,” which are business managers, HR specialists, and data scientists working together to use data to improve employee-related decisions and practices.
Link for article: https://hbswk.hbs.edu/item/companies-love-big-data-but-lack-strategy-to-use-it-effectively
The article of my choice is “Why Artificial Intelligence Isn't a Sure Thing to Increase Productivity”
ReplyDeleteLink: https://hbswk.hbs.edu/item/artificial-intelligence-tools-won-t-automatically-increase-productivity
The author of article said that the usage of artificial intelligence tools requires the ability and skills of people to use them. Adding AI tools does not automatically increase performance if people who use them do not use the technology correctly. So far, there are no studies that would indicate what skills employees need to have to use tools based on artificial intelligence. Choudhury intends to conduct such research and point out the complementarity between human capital and machine learning.
Choudhury conducted a survey at the US patent office, where he proved that it does not matter which technology is applied. It was important whether a person has IT and engineering skills. Many companies spend huge amounts on introducing artificial intelligence and count on immediate improvement of efficiency and reduction of errors. In the vast majority, they are used by people without IT experience.
The article emphasises that companies must take into account the need to train employees because they risk the failure of their technology. Using these tools without knowledge only reduces productivity and increases errors. This does not mean that only IT specialists are fit for work. The current employees should be intensively trained.
In addition, in autumn, a more accurate study / experiment will be conducted with the participation of 1,000 people.
I have chosen the following article „ The Civic Benefits of Google Street View and Yelp”. Here is the link to the article https://hbswk.hbs.edu/item/the-civic-benefits-of-google-street-view-and-yelp.
ReplyDeleteThe author states that the data which is being constantly generated in the world, have the potential to improve, develop and help in evaluating and understanding the real world better. Nowadays, there are the vast amounts of data so the knowledge how to use it becomes extremely important. A dataset may be used several times for many application. The following examples were presented in the paper: Google Street View and Yelp. The mentioned companies collected the data for their purpose but it can be used for other aims as well.
As you probably know, Google street View is a technology that provides panoramic views from positions along many streets in the world. In the reviewed research the images of New York streets obtained from Google Street View were also used to teach the computer to recognize some features like driveways, sidewalks and etc. Additionally, the dataset was labeled with income and the machine learning model was trained to associate between the mentioned features and the incomes. The solution may be applied in the cities where population surveys are conducted every several years in order to improve data assessment thus making their policy more flexible.
The second example which was presented in the research paper is Yelp. Yelp is a local-search service powered by crowd-sourced review forum mainly about restaurant. The dataset including reviews was used to find the restaurants which should be inspected. Searching a dirty restaurant was based on the analysis of specific word combinations in such a way that the model was trained to recognize the problematic restaurants.
In my opinion using the same datasets in multiple application may provide promising results opening new horizons in fundamental and practical data science. Certainly, there are some problems associated with this idea – machine learning is not a panacea, the models should be designed in accordance with the particular subject field it is going to be used in. Nevertheless, scientific literature provides numerous evidences of civic benefits in cases when a model is thoroughly planned and adjusted for use in specific area.
Some people think that big data can solve every problem. In my point of view this statement is not completely truthful nowadays. However, proper gathering of big data allows to collect more information and it would let to solve more and more problems in the future. I think that there are more civic benefits than disadvantages of big data approach. Even if some part of people can lose their jobs due to the fact that company will not need them (for example person who carry out surveys in the future), they will still be able to find another job which is needed.
The article that interested me is "What Should Mark Zuckerberg Do?", Facebook's popularity has been falling for several years. But Zuckerberg is also the owner of Instagram and Tinder. and many other small projects. Unlike Facebook, Instagram popularity is growing rapidly. This year, the instagram has been recognized as one of the best investments in the world(was bought for 1 billion dollars. and its current price is about 100 billion dollars). But given the scandals around Zuckerberg , there is a possibility that his fate will befall Elon Musk. Already this year there were scandals, with the leakage of personal information of users from Facebook, as well. with the Facebook advertising algorithm that was used to send out fake news, and many more. Zuckerberg already spoke to the US Senate. I think in the near future, the management of Facebook will be revised.
ReplyDeleteI have chosen an article "Companies Love Big Data But Lack the Strategy To Use It Effectively"
ReplyDeleteNowadays, all the larger companies collect an incredible amount of information. As the amount of information grows faster and faster, there is a problem with its use. The problem is that, in many cases, big data is not used well. Companies are better at collecting data–about their customers, about their products, about competitors than analyzing that data and designing strategy around it. There is also a fear of what we will do with so much data if the Internet of things continues to grow. Using such data and making business decisions on this basis will be one of the most important things for all relevant companies. It can also be useful in sport and medicine and change the life of each one of us.
“Health care is rife with examples like these—and such applications of big data will only expand over the coming years. I spend a lot of time thinking about questions like, How will artificial intelligence change the medical diagnostics industry? How will better data collection transform the ways in which we do clinical trials for new cancer drugs? It is both staggering and exciting to imagine how data and analytic capabilities will transform entire industries and it was thrilling to engage in these conversations with folks from such rich and diverse backgrounds.” Ariel Dora Stern
Sorry, I forgot about the link to the article
Deletehttps://hbswk.hbs.edu/item/companies-love-big-data-but-lack-strategy-to-use-it-effectively
I chose What Should Mark Zuckerberg Do?
ReplyDeleteData shared on community poratalch should be carefully protected.
We are all aware of the fact that posted photos and information
are used by people (criminals) for "bad" purposes.
For sure, current facebook needs remodeling.
Today, not everything can and must be free.
However, you should officially give what and how much it costs,
or how to earn it, so that users are conscious users!
I have chosen the article:
ReplyDeletehttps://hbswk.hbs.edu/item/is-apple-s-real-privacy-challenge-technology-innovation-itself
This article is very interesting indeed. Is it good that Apple wouldn' like to share the data with the bureau when it comes to the crime suspicion, but can share the data with third companies to earn more money? Where is the border of what is ok, and what is too far?
The additional fact to take into consideration that something has changed apparently. A few days ago Apple's CEO said:
(based on BBC)
I selected Why Artificial Intelligence Isn't a Sure Thing to Increase Productivity from: https://hbswk.hbs.edu/item/artificial-intelligence-tools-won-t-automatically-increase-productivity
ReplyDeleteThe article is about the experiment comparing productivity of workers examining patent applications depending on their educational background. Students where divided into two groups, one was given a Boolean search tool and the other a sophisticated AI tool. Furthermore, halves of each group had access to an expert advise. The task was to examine patent application to check if it's really innovative and similar idea haven't existed before.
The experiment shown that no one succeed without an expert advise. Results of those who had an access to experts depended on their educational background and a tool used. Those with a Computer Science related degree did better with an AI tool while others were more effective with a Boolean search tool.
Of course the article is not scientific so it was expected but still experimetnal setup is lacking important details and the results sound manipulative. The article states that AI tool was accepting a whole document (paten application) as and input and providing related documents as an output. Considering such interface it seems unreasonable that any background in Computer Science was necessary to use such tool. If the results obtained by subjects using this tool was indeed worse then the tool itself should be examined. Maybe suggestions made by the tool were irrelevant and it may has nothing to the educational background of subjects.
This comment has been removed by the author.
ReplyDelete
ReplyDeleteI have chose "What Should Mark Zuckerberg Do?".
The huge success of Facebook comes from the fact that it is widely available and free.
People do not know the term TANSTAAFL (https://en.wikipedia.org/wiki/There_ain%27t_no_such_thing_as_a_free_lunch).
That if something is available without charges, it must be earning something differently.
In the case of Facebook, user is the product. They are selling information about their users.
As long as the principles of such cooperation are clearly defined and understood by users, everything is fine.
Worse, if large corporations such as Facebook violate our trust and try to maximize profits at our expense (https://en.wikipedia.org/wiki/Facebook-Cambridge_Analytica_data_scandal).
In my opinion, Facebook should introduce paid subscriptions in exchange for more privacy.
I have chosen the article:Online Match-Making with Virtual Dates
ReplyDeletehttps://hbswk.hbs.edu/item/online-match-making-with-virtual-dates
There are many people who have found their other halves via the Internet. However, the current models used to connect people in pairs are very artificial, static and distant from real interpersonal interactions. Currently, dating sites are designed as if searching for love was a variation on online shopping. People spend too much time looking for a person with whom they can go for a coffee instead of getting to know people through conversation. They are often disappointed after their first meeting because someone has not turned out like they expected. Online dating allows for long-term formation of ideas about a partner that is not real because no social feedback is obtained, everything is a figment of one's imagination. People are searching using criteria, but they don’t include subtleties that only appear when you meet someone.
That's why researchers came up with the idea of virtual dates. If two portal users find a good match between themselves, the couple will meet on a 5-minute date by computer. The date is some sort of ice-breaker. Thanks to this, they can capture certain nuances such as reacting to certain words, behavior, etc. Virtual dates provide auditory and visual experiences, thanks to which people can interact with each other as if they were on a real date in a museum or gallery. They can share their views and opinions on a given topic. It is not dry conversation via the communicator, where they don’t know how to start a conversation.
Idea standing behind virtual dates can be used to develop applications that allow people with similar interests to form new friendships and relationships. There is also possibility to create applications for older people, which allow them to meet other people and not feel lonely.
I think that the idea of virtual meetings is very interesting and helps to overcome shyness when getting to know each other. It also helps to better assess our interest in the person. However, one should remember not to limit the search for love or friendship only to the Internet because virtual dates can’t substitute real experience of meeting someone face to face, no matter how real they can become.
Hi,
ReplyDeleteIt was very inspiring for me to read “Water, Energy and Transportation: Preparing for the Population Boom” (https://hbswk.hbs.edu/item/water-electricity-and-transportation-preparing-for-the-population-boom).
I’ve been working in energy sector for 18 years, so this issue is double interesting for me, not also because of my private ecological interests. What we’re searching now, are holistic solutions for both public and private markets, in order to provide not only appropriate resources, but also their optimal configuration. This is a huge challenge for contemporary IT.
This article presents a very good summary of those three powers usage. As for energy, there are two thoughts given to analyze and to inspire to do something with: our buildings are not energy efficiently prepared, and people are not saving energy (and not open to any change in this respect).
In respect of water, I didn’t think before that it works like most of it is used for industrial purposes, only small percentage of that goes to our everyday usage.
As for transportation, definitely this is a permanently growing problem, which can be solved with using respective IT solutions.
A sustainable and affordable energy supply, a safe access to clean water and an efficient environmental protection: information and communication are together the issues to be taken into consideration. The industrial clients and public-sector customers expect urgently high-performance IT solutions which have an “superordinate” perspective approach enabling holistic solutions for all the problems mentioned in the article and other details, connected to them.
Because the issues are fundamental to survive in many-years-forward perspective, I reccomend to think it over, but first to read this article.
Have a nice evening :-)
This comment has been removed by the author.
ReplyDeleteI choose „The Civic Benefits of Google Street View and Yelp”.
ReplyDeletehttps://hbswk.hbs.edu/item/the-civic-benefits-of-google-street-view-and-yelp
The article presents the benefits of data generated by people around the world. The author in his publication focuses on the Google StreetView and Yelp applications.
Currently almost everyone has a smartphone with installed applications that generates huge amounts of data. This data can be used to improve the lives of people in the cities. Available opinions on given places allow you to choose, for example a restaurant that serves the best dishes in the city. Traffic monitoring allows you to choose the fastest route to your home or store bypassing congested streets and city authorities to improve communication by changing the traffic organization or by setting additional traffic lights. Good data usage can be beneficial for the city's development.
https://www.tvn24.pl/katowice,51/inteligentna-sygnalizacja-swietlna-gliwicki-sposob-na-korki,361922.html
I've choosen "Two Decades Later, is the 'New Economy' Finally Here?" https://hbswk.hbs.edu/item/two-decades-later-is-the-new-economy-finally-here
ReplyDeleteThe article is revisits question from an older one, 2000 "Whither the Information Economy?", which seems to be induced by 1982 "Information as a Resource".
Enthusiasm and pesimism intertwine in this article. Author notes that "New Economy" did not deliver "the promise of significantly greater productivity and growth through technology".
On the other hand, notes the existence of "Exponential Organizations (ExOs)" - entities that grow in financial performance with exponential rate while maintaining employment on same levels. Other reviewed book conclude we witness the shift from physical economy "atoms/bricks" to information-based "clicks/bits".
I disagree the "New Economy" is something radically different and having potential of unbound growth. Of given examples of ExOs (Google, Netflix, Airbnb, Amazon) - only two have strong base - Amazon with its retail encompassing new and new areas, and Google that want to collect and process all the data it can.
Airbnb (and also Uber) acts as a mediator between customers and suppliers, and both customers and suppliers can switch to other - better or cheaper - mediator without thinking twice. Netflix depends on goodwill of the movie studios, and can be strangled by them in no time. I think all this exponentiality observed is just temporary adjustment due to slightly better planning and operations in some cases, and result of shifting costs onto sub-contractors in other - not sustainable.
What really matters - agriculture, construction, textile, semiconductors, steel and plastics - it is all still bound by matter and energy input, and this will not change soon.
I have chisen an article "Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change". I was interested how to measure a gentrification for scientific purposes. The authors explain how data from yelp may be used to forecast changes in hose prices. They also analyse how openng a new store or cafe may change the local demographic. It is quite interesting study where we can see that correlation can help topredict something but we do not analyse the causation.
ReplyDeleteI am finding most interesting the article 'Companies Love Big Data But Lack the Strategy To Use It Effectively'. Author if the article is deliberating about different strategies and approaches of companies that are implementing big data technology in real world business cases. The problem is that, in many cases, big data is not used well. Companies are better at collecting data–about their customers, about their products, about competitors– than analyzing that data and designing strategy around it.
ReplyDeleteRelated articles
https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/how-companies-are-using-big-data-and-analytics
https://www.cio.com/article/3003538/big-data/study-reveals-that-most-companies-are-failing-at-big-data.html
https://infocus.dellemc.com/william_schmarzo/5-steps-to-building-a-big-data-business-strategy/
I’ve chosen an article: „Why Artificial Intelligence Isn't a Sure Thing to Increase Productivity” (https://hbswk.hbs.edu/item/artificial-intelligence-tools-won-t-automatically-increase-productivity).
ReplyDeleteThe author of the article believes that the use of Artificial Intelligence does not have to increase the efficiency of human work. It depends on computer science experience of the employees. Even if the given tool will be a great tool, employees will be still less productive.
Choudhury claims that employees without computer science background should have extensive training to use machine learning tools efficiency. In connection with this conclusion he expands the area of his research and tries to find out whether these people will catch up and the productivity gap narrows.
In my point of view the selected statistical group is too homogeneous. Undoubtedly, such research is a good contribution to further study of the problem, which perhaps is not repetitive in another environment. I agree with Adam that the cause of the problem is in the tool itself rather than in its operator. If such tool will be used by people without computer science experience, it should be just well prepared. I think it does not depend on the user’s background.
I have chosen the following article:
ReplyDelete"10 Reasons Customers Might Resist Windows 8" from:
https://hbswk.hbs.edu/item/10-reasons-customers-might-resist-windows-8
The article presents some reasons why people might resist Windows 8. It mainly consists of losing control over the system, difficulties with learning how to use it properly, and aversion to changes.
I could agree with them, but I got rid of the Microsoft's system before the appearance of windows 8, because I wanted to have more control over the system, so I have never had an opportunity to check how well the system worked.
The only thing I know about Winodws 8 system is it has terrible and non-functional tiles.
I tried Windows 8 at my university once and for me in, user interface was unfriendly and very confusing.
In fact, as we can say after almost 6 years, Windows 8 was not welcomed well. People found it strange and hard to work with. The next version – Windows 10 – returned to the old look, without all these files, with the big Start button in the left corner.
Moreover, this is not the only failure of the Microsoft - usage share of operating systems on mobile devices is less than 1%.
As we can say after reading described article, sometimes putting too much effort in changing the product may results in dismissal it by consumers.
I chose this article,
ReplyDeletehttps://hbswk.hbs.edu/item/the-business-of-free-software-enterprise-incentives-investment-and-motivation-in-the-open-source-community.
One could say that hell has frozen. Once Microsoft considered free software, including Linux, to be the main threat to itself. Since then, a lot has changed and not only does the giant look much more favourably at free software. Microsoft recently joined the Open Innovation Network (OIN). OIN is an association of several companies and institutions (including Google, IBM, Novell, Philips, Red Hat, Sony and SUSE), whose task is to acquire and make available Linux patents in exchange for waiving claims against technologies used in Linux. After Microsoft's accession to the OIN, everyone will be able to use Microsoft's 60,000 software patents for free.
My last post did not appear here, I am posting again
"Learning Curve: Making the Most of Outsourcing"
ReplyDelete(https://hbswk.hbs.edu/item/learning-curve-making-the-most-of-outsourcing)
Outsourcing was falsely advertised as a way around on-the-job training, managing human resources and other "non-productive" costs associated with hiring people to do the job as employees. It turns out, that there are limits to what can be done with labor-as-commodity. It has been shown before, e.g. in the case of the Amazon Mechanical Turk (a massive crowdsourcing platform for HITs - Human Intelligence Tasks), that in some cases building expertise is indispensible. The above article is another argument in this discussion.
The articule I chose touch important topic: How data driven decision changing one industry over another. First not obvious is Sport: „New Zealand’s yacht designers and crew prepared for the 1995 Americas Cup with a radical, data-intensive experimental design.” Another example from this field: „German soccer team TSG Hoffenheim deploys analytics in scouting and player development.”
ReplyDeleteNaturaly the best place to use data driven decison is business, where objectivity is so important. The advantage of this sector are data itselfe. Companies are gatering all avaiable data, because with current technology it's cheap and process is well know. But it's not enough, rough data will not magically speak for them selfs. This is where some companies hit the wall, they don't have strategy how to use all valuable data, that could answered all the question.
Article mentions also new approche to creat multidisciplinary team called “people analytics,” which are business managers, HR specialists, and data scientists working together to use data to improve employee-related decisions and practices.
Link for article: https://hbswk.hbs.edu/item/companies-love-big-data-but-lack-strategy-to-use-it-effectively