Tag Archives: Know
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Late last week, Tumblr’s app disappeared from Apple’s App Store with no explanation of why. Now we know.
As first reported by CNET late Monday, the cause was the fact that people were able to upload photos of child sexual abuse to the image-sharing service. The publication noted that the lack of explanation at the time of Tumblr’s removal was likely due to necessary coordination with law enforcement.
Tumblr has now updated its issue page for the iOS app’s removal with a statement saying it has “a zero tolerance policy when it comes to media featuring child sexual exploitation and abuse.”
The service, which is owned by Verizon subsidiary Oath, said it works with industry peers and authorities to actively monitor the images uploaded to it.
“Every image uploaded to Tumblr is scanned against an industry database of known child sexual abuse material, and images that are detected never reach the platform,” it said. “A routine audit discovered content on our platform that had not yet been included in the industry database. We immediately removed this content.”
At the time of writing, Apple was yet to restore Tumblr’s app to its iPhone and iPad repository.
Tumblr has been involved in several cases of child sexual abuse material being posted online. A recent example included an Ohio police sergeant who used the service to share an image of a naked boy.
Knowledge is power but much depends on how asymmetric it is: what do you know that others don’t and vice versa. Below are four strategically different levels of know-how plus some of the strategies you can use to leverage each to advantage.
The complex issue of handling asymmetric information is central to the field of game theory– a rigorous analytic discipline used widely in economics, business, strategy, political science, law and more. I’ll address here the mind-twisting problem of how much you know about what others do and don’t know, and conversely, what they know about what you do and don’t know. This may seem esoteric but we encounter such issues daily. Let’s start simple and then build up the layers of asymmetric know-how.
Level 1: Only You Know About a Misdeed. Suppose you find out that your main competitor has stolen some of your intellectual property (IP) or other assets, and is using this against you. It could be some proprietary software, a customer list, a supplier contract, wage scales, your pricing strategies, or other confidential know-how. Often the IP thieves will be within the organization, as happened to the National Security Agency and numerous companies in such fields as oil & gas, agricultural seeds, and all manner of technology. The U.S. Department of Commerce estimated that IP theft has accounted for trillions in lost value. Much of this comes from industrial espionage by outsiders as well, especially China, although many countries and rivals play this game.
Your first reaction when learning that your secrets were stolen may be to cry foul and call the lawyers. But there may be advantage in you knowing something about their misdeeds while they don’t know that you know. First, you could infringe some of their IP as payment in kind, with a soft hint that two can play this game. This may lead to tacit collaboration, a formal licensing arrangement, or conflict resolution less costly than an ugly shoot out at high noon with legal gun slingers. Also, reconciliation can build understanding, trust or even empathy. For example, when parents find out that their young child stole some of their cash, smoked pot or drank alcohol, they can jump all over the kid or gently signal awareness, in ways that allow for face saving self-correction and maturation of the child.
Level 2: The Other Party Knows You Know. Suppose, however, that your competitor finds out on its own– without you having informed them– that you know that they have violated your IP. What should you do in this symmetric knowledge situation about the violation? First, it may not be truly symmetric because the rival may not know that you know that they know. This is akin to a child knowing that his parents found out about the smoking or drinking, while still being unsure about whether they know that he knows that. For example, it could be that the maid told the child that the parents know. As before, it may be wise to keep such meta-knowledge (i.e. what each of you know about what the other knows) asymmetric since the situation may automatically correct itself. The child will either stop his misdeed or become even more devious perhaps– although he now realizes that his parents are not as clueless as he previously assumed.
Level 3: A Child Knows His Parents Know that He Knows. Suppose that the child discovers, perhaps from the maid, that his parents now know that he knows that they have uncovered his nefarious deeds. This would be embarrassing, even though some semblance of ignorance can still be feigned, since his parents have not directly confirmed this by confronting him. Perhaps the maid lied and is playing her own game to get the child to cease his infractions, concerned that the parents will blame her for not telling them. Without complicating this layer cake further, with the maid’s varying degree of knowledge and hidden agendas, it should be clear that knowledge asymmetry can happen at multiple levels.
The first is knowledge about presumed acts of behavior (such as an IP infringement). The second level concerns the parties’ awareness about what the other side knows and doesn’t know. The game theory aspects of just the two-party conflict becomes more complex at this higher strategic level. It will seldom be optimal to put all cards on the table if tactical advantage is the aim, since judicious signaling, while avoiding loss of face, may lead to better outcomes. In international negotiations about violations of trade agreements, for example, a piecemeal approach may lead to better outcomes than fully escalating the conflict with hurt egos and further recriminations.
Level 4: Full Parity – Everybody Spills the Beans. Suppose, however, that parents tell their child that they know he knows that they know; the strategic situation now will reach a different level of meta-knowledge yet. If the indirect approach mentioned in level 3 does not work, then in anything from corporate disputes to child rearing to marital infidelity, it may pay to put all cards on the table. If restricted to one single issue, such as a stolen customer list or a child smoking pot, talking it all out may–perhaps with the help of a professional counselor–be cathartic. But when multiple issues are at stake, or if there are more than two aggrieved parties, the situation may call for seasoned negotiators who know when to separate or combine issues. One problem is that you will never know for sure that everyone has shared all they know, although legal clauses with punitive damage levels may get you close.
The general advice in complex cases of conflict is to pursue principled negotiations rather than positional bargaining, as explained in Getting to Yes. Try to agree on the principles that should govern the issue to be negotiated, such as trade dispute or a salary raise, before haggling about dollars or concessions as though you are in a bazaar. For example, should the primary reference point when hiring new managers be their past salary, your own internal payment scale, or the amount an outside party is offering them? Once you agree on that in principle, the remaining negotiation will be much easier. Also remember that good negotiators spend more time understanding the other side’s hopes, fears, and context than just their own agendas, plus any knowledge asymmetries that might exist.
What are the three most important things non-programmers should know about programming? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world.
Early in my web development career I realized that there were three things that were critical for every non-programmer to know before interacting with programmers in a professional setting.
My experience building a single feature with a non-technical product manager taught me these lessons almost immediately.
Let me explain…
I was working with Colin, a non-technical product manager who was responsible for driving the direction of the product and working with my team, the development team, to implement features for our product.
As a developer, Colin was great to work with. The feature requests he created were always really well thought out. He always had all the edge cases accounted for and he drew detailed wireframes, diagrams of what the expected behavior of the feature should look like.
But then, all of a sudden, Colin had a feature request for our team that caused a major problem for our entire development team!
Colin gave our team a wireframe diagram of our application that had an additional checkbox that would allow a user to store their credit card information on the platform.
The feature request seemed simple enough, but because of laws and regulations about credit card information (specifically PCI compliance laws), storage of credit card information is something that is highly complex and regulated.
Despite seeming simple, supporting this one feature in our application would require a complete rewrite of our code.
I brought this issue up to Colin and at first he didn’t get it. “All I’m asking for is a simple checkbox, it can’t be that difficult to add”, he said. I explained that adding the checkbox would be super easy, but making the checkbox do what it claimed would be the difficult part.
Colin then did something that proved that he was the type of product manager who got things done.He explained, “Let me explain why I wanted to include the ability to allow a user to save their payment information…” and then Colin explained that after making a certain type of purchase, it was very common for users to make a related purchase shortly after.
Together we realized there was a solution where we could prompt the user to purchase both items at the same time, instead of worrying about storing the payment information. This was a solution that would give Colin everything he wanted and be ten times easier to implement for our team.
Together with Colin, we implemented this solution. This experience taught me that there are only three things that non-programmers need to focus on when working together with other developers.
They’re also easy lessons to learn…
1. Communicate the technical details to developers quickly and efficiently.
There is no more effective way to explain functionality of an application than showing a developer wireframes of proposed changes.
2. Things can appear to be easier to implement than they actually are.
Be open to the idea that things that seem like they should be really easy can be much more difficult to implement in practice.
3. Provide context about why you think things are important.
Explain the why behind the thoughts you have in situations where you’re getting pushback from developers — if you do this you’ll find yourself working together with them to solve problems.
Remember that you are have the same end goal as the developers you’re working with — to provide the best experience possible or the application you’re building.
Follow these steps and the developers you’re working with can focus their energy on being the best developer they can be. And if you’re a developer you can focus on the.
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I’m a baseball fan. When I lived in the Bay Area, I was a season ticket holder to the San Francisco Giants. And every baseball fan knows about Pete Rose, the preternaturally talented player who scandalized his sport when it was revealed he bet on baseball, including games involving his own team. Now, no one is contemplating allowing players or managers to bet on games in their own sport. But the Pete Rose story serves as a grim reminder of what can happen with sports gambling.
The trouble is that sports gambling is fun! The thrill of making some dough on your team just adds to the excitement of the sport. It’s also hugely profitable for business and government. So when the Supreme Court of the United States released their decision on Murphy vs. NCAA last week, the gambling-loving world rejoiced. SCOTUS determined that the 1992 federal law called Professional and Amateur Sports Protection Act (PAPSA) violated the Constitution’s anti-commandeering clause, thus striking down the law.
Mark Conrad is a professor of law and ethics at Fordham University, where he has taught in the School of Law and in the Gabelli School of Business. He’s also the director of Gabelli’s Sports Business Concentration, and is the author of The Business of Sports -; Off the Field, In the Office, On the News. Professor Conrad was kind enough to share with me some of his thoughts on this landmark decision.
1. Nothing’s Actually Changed…Yet.
The Court’s decision caused an avalanche of news and commentary, but, “At the moment, not much has changed,” says Conrad. The decision opened the door to huge change, but nothing is actually different yet. Conrad explains, “The court declared unconstitutional the Federal law that prohibits sports gambling. It did not sanction or permit sports gambling.” So what happens now? Conrad says no one really knows: “It is now up to the states, or the federal government, to decide.” Here’s where it get interesting!
2. The Devil Is in the Details.
“This story is only beginning,” says Conrad, who also has a degree from Columbia’s School of Journalism. “No state has enact a gambling scheme, although New Jersey may soon,” he says. The question is what happens next. For starters, Conrad asks, “Will states legalize it? And if so, which ones, and when?” Next comes the what. Conrad wants to know, “Will it apply to all sports or just pro sports?” And finally, the how. Conrad ponders: “What will be the license fees for companies wishing to do business in the state? Taxes? Anti-corruption measures?” The potential complexities are endless.
3. Congress May Not Be Done.
The Court may have struck down Congress’ PAPSA law, but that doesn’t mean Congress can’t still have the final word. Conrad explains, “The problem with PAPSA was it prevented states from exercising their powers. The law did not mandate a ban on sports gambling – rather, it told the states they were not allowed to enact laws ‘authorizing’ such gambling schemes.” The problem was the way this law was structured, but not the idea behind the law. In fact, Conrad says, “The decision did state that Congress has the power to enact a ban on gambling.” It’s possible Congress could throw some very cold water on all the excitement.
4. Integrity May Be an Issue…Or May Not.
The potential implications for the integrity of sport are fascinating. As with any gambling, there’s risk of corruption. Conrad recalls, “It has occurred in the past, notably in point-shaving in college sports.” But cheating isn’t a given. “In fact, the risk of corruption may decrease with a properly regulated integrity oversight,” Conrad explains. There are examples the US could look to for inspiration. Conrad says, “The UK model has worked well. The betting companies engage in analytics and metric systems to police suspicious gambling patterns and report these anomalies.” The key is not to over-regulate or over-tax it, which may push otherwise legal gambling underground.
5. This Decision Could Have Major Implications for State Versus Federal Authority.
“This is the underlying constitutional issue in this ruling,” Conrad explains. “Ultimately, it is a constitutional law case regarding state powers under the Tenth Amendment.” Here’s his plain-English explanation of the finer constitutional points: “PAPSA was problematic because it ‘commandeered’ states rights. Instead of banning sports gambling, it said could not enact laws authorizing gambling. It’s a subtle difference, but a constitutionally defective one.” This is an important decision in part of a greater shift. According to Conrad, “It continues a trend to give greater deference to state sovereignty.” It will be fascinating to watch as the complexities continue to develop.
Other than that, Mrs. Cannon, how was the flight?
A lot of things went wrong on Leighton and Merry Cannon’s recent trip to Europe on American Airlines. But, as Merry Cannon said in a phone call, the worst part was probably right at the very end: when she discovered a dead rat in her checked luggage.
Yes, a dead rat–“smashed,” as she put it–yet hidden, so that she wasn’t sure what was creating the “disgusting” smell that came from her bag when she picked it up at the airport. She brought it home unwittingly, despite the odor, hoping to clean and salvage at least some of her clothes.
“It smells like a dead body.”
The story began early March 5, as Merry Cannon told it. Her husband had a business trip in Germany and France, plus a short visit to London to see family. Since his mother was free to come to their house in Arkansas to take care of their two small children for a few days, Merry decided to go along.
Travel troubles mounted quickly: delayed and canceled flights, missed connections, an unplanned overnight stay in Chicago after their flight to Germany left without them, while American tried to find room for them on any airplane to Europe. Ultimately they had to fly to Brussels, Belgium instead, forgo the German part of their trip, and arrange to drive a rental car to Lille, France.
When they arrived in Belgium, however, they found that their luggage had never left Chicago. It didn’t catch up to them until their last night in France, just before their morning flight to London to see family for the day before heading back to the U.S.
Eventually, they made it home to Arkansas, and Merry collected their bags. The smell now emanating from her luggage nearly knocked her over, she said.
“Smell this,” she said to her husband.
“It smells awful!” he replied.
“It smells like a dead body.”
“It smells so gross.”
Maybe it’s “just” sewage waste from a lavatory
Leighton tried to sanitize the handle with Clorox wipes. They brought the bag to a customer service agent, who speculated that maybe it had been left on a runway in the rain at some point during the five days it took to catch up with her, and the smell was from mold.
Merry said she was skeptical, as they hadn’t noticed a smell when the luggage caught up to them in France. Perhaps, the customer service agent suggested, it had been stored under a lavatory on the plane, and sewage waste had dripped onto it.
Disgusted by that idea, Merry Cannon asked for a garbage bag or something to avoid taking the bag. But the agent told her the airline would only compensate her for destroyed luggage if she first brought everything home, tried to wash it, and offered evidence that it didn’t work.
The Cannons threw the bag in the back of their truck, and left it on the back porch of their house when they got home. The next morning, Merry Connor opened it, pulled out a few articles of clothing, and held her nose. She dropped them in the washing machine with vinegar, bleach, Tide, and OxiClean.
It barely had an effect. Disgusted, she walked back to the porch. And then she saw the dead rat.
Her reaction: “I’m surprised the people next door, building a house–the construction workers–didn’t call the police. I screamed, ran inside, started washing my hands over and over. I was just crying.”
“Your biggest concern would be bubonic plague”
She called American Airlines. They told her to photograph everything in the bag, and to put in a claim. The person she spoke with at the airline was apologetic, she said, and promised that the airline would pay for everything.
Then she called the county health department.
“This is awful,” she said the health department official told her when she described the rat situation. “I’ve never heard of anything like this. Your biggest concern would be bubonic plague.”
“The plague? What am I, in a sitcom?” She thought about her two young children. Had she unwittingly brought a bubonic plague-infested rat into their home?
“Rats carry the plague,” the heath official told her. “Your other worry would be fleas. That’s what carries disease.” Later, he added, “Burning garbage is illegal, but that bag needs to be burned.”
Merry and Leighton took photos, and disposed of the bag and its contents. She said she hoped American Airlines would make her whole–at least for the actual value of the things she lost.
“I realize this is not the outcome you requested”
An American Airlines representative emailed her, saying the airline would pay her $ 1,648, “maximum liability set by the Montreal Convention … for a trip with an international flight.”
“I realize this is not the outcome you requested,” said the note, which was signed by a “specialist, central baggage,” in the Central Baggage Resolution Office. “[H]owever, I appreciate this opportunity to address your concerns and explain our position. We hope you will give American Airlines another chance to earn your business.”
I asked American Airlines for comment. Here’s their statement:
We have apologized and are not aware of any similar issues of a rat making its way into a checked bag before. While we are unable to determine if the issue occurred in the United States or overseas, we did apologize to the customer, and they were compensated earlier this month.
NOTE: Based on the Montreal Convention and applicable international tariffs, liability limitations for international travel are 1,131 Special Drawing Rights (SDR) per ticketed passenger. This applies to all airlines for international travel. SDR (Special Drawing Rights) is an International Monetary Fund unit of currency. SDR’s will be converted to U.S. Dollars using the rate in effect on the mishandled baggage settlement date. That is what was compensated. If you convert 1,131 to U.S. dollars, it is around $ 1,600.
It wasn’t enough, Merry Cannon replied. The bag itself was a Samsonite that cost $ 300, she said, and she had three pairs of boots that cost $ 200 each, “plus I had dressy clothes, and workout clothes.” Some of the things she’d brought were brand new, and stillahd the tags on them.
Cannon said she tried several more times to get someone from American to discuss her case, and see if she could get anything beyond the $ 1,600, but to no avail. Eventually, she posted the photo of the rat and her story on Facebook and Twitter.
“You could have just paid me for my bag, and none of this would have been out here,” she said. “I’m never flying with them again.”
IPsoft is, in many ways, an unusual entrant into the crowded, but burgeoning, artificial intelligence industry. First of all, it is not a startup, but a 20-year-old company and its leader isn’t some millennial savant, but a fashionable former NYU professor named Chetan Dube. It bills its cognitive agent, Amelia, as the “world’s most human AI.”
It got its start building and selling autonomic IT solutions and its years of experience providing business solutions give it a leg up on many of its competitors. It can offer not only technological solutions, but the insights it has gained helping businesses to streamline operations with automation.
Ever since IBM’s Watson defeated human champions on the game show Jeopardy!, the initial excitement has led to inflated expectations and often given way to disappointment. So I recently met with a number of top executives at IPsoft to get a better understanding of how leaders can successfully implement AI solutions. Here are four things you should keep in mind:
1. Match The Technology With The Problem You Need To Solve
AI is not a single technology, but encompasses a variety of different methods. In The Master Algorithm veteran AI researcher Pedro Domingos explains that there are five basic approaches to machine learning, from neural nets that mimic the brain, to support vector machines that classify different types of information to graphical models that use a more statistical approach.
“The first question to ask is what problem you are trying to solve.” Chetan Dube, CEO of IPsoft told me. “Is it analytical, process automation, data retrieval or serving customers? Choosing the right a technology is supremely important.” For example, with Watson, IBM has focused on highly analytical tasks, like helping doctors to diagnose a rare case of cancer.
With Amelia, IPsoft has chosen to target customer service, which is extraordinarily difficult. Humans tend not to think linearly. They might call about a lost credit card and then immediately realize that they wanted to ask about paperless billing or how to close an account. Sometimes the shift can happen mid-sentence, which can be maddening even for trained professionals.
So IPsoft relies on a method called spreading activation, which helps Amelia to engage or disengage different parts of the system. For example, when a bank customer asks how much money she has in her account, it is a simple data retrieval task. However, if a customer asks how she can earn more interest on her savings, logical and analytical functions come into play.
2. Train Your AI As You Would A New Employee
Most people by now have become used to using consumer facing cognitive agents like Google voice search or Apple’s Siri. These work well for some tasks, such as locating the address for your next meeting or telling you how many points the Eagles beat Vikings by in the 2018 NFC Championship (exactly 31, if you’re interested).
However, for enterprise level applications, simple data retrieval will not suffice, because systems need domain specific knowledge, which often has to be related to other information. For example, if a customer asks which credit card is right for her, that requires not only deep understanding of what’s offered, but also some knowledge about the customer’s spending habits, average balance and so on.
One of the problems that many companies run into with cognitive applications is that they expect them to work much like installing an email system — you just plug it in and it works. But you would never do that with a human agent. You would expect them to need training, to make mistakes and to learn as they gained experience.
“Train your algorithms as you would your employees” says Ergun Ekici, a Principal and Vice President at IPsoft. “Don’t try to get AI to do things your organization doesn’t understand. You have to be able to teach and evaluate performance. Start with the employee manual and ask the system questions.” From there you can see what it is doing well, what it’s doing poorly and adapt your training strategy accordingly.
3. Apply Intelligent Governance
No one calls a customer service line and asks a human to talk to a machine. However, we often prefer to use automated systems for convenience. For example, when most people go to their local bank branch they just use the ATM machine outside without giving a thought to the fact that there are real humans inside ready to give them personalized service.
Nevertheless, there are far more bank tellers today than there were in before ATMs, ironically due to the fact that each branch needs far fewer tellers. Because ATMs drastically reduced the costs to open and run branches, banks began opening up more of them and still needed tellers to do higher level tasks, like opening accounts, giving advice and solving problems.
Yet because cognitive agents tend to be so much cheaper than human ones, many firms do everything they can to discourage a customer talking to a human. To stretch the bank teller analogy a little further, that’s almost like walking into a branch with a problem and being told to go back outside and wrestle with the ATM some more. Customers find it incredibly frustrating.
So IPsoft stresses to its enterprise customers that it’s essential that humans stay involved with the process and make it easy to disengage Amelia when a customer should be rerouted to a human agent. It also uses sentiment analysis to track how the system is doing. Once it becomes clear that the customer’s mood is deteriorating, a real person can step in.
Training a cognitive agent for enterprise applications is far different than, say, Google training an algorithm to play Go. When Google’s AI makes a mistake, it only loses a game, but when an enterprise application screws up, you can lose a customer.
4. Prepare Your Culture For AI As You Would For Any Major Shift
There are certain things robots will never do. They will never strike out in a little league game. They will never have their heart broken or get married and raise a family. That means that they will never be able to relate to humans as humans do. So you can’t simply inject AI into your organizational culture and expect a successful integration.
“Integration with organizational culture as well as appetite for change and mindset are major factors in how successful an AI program will be. The drive has to come from the top and permeate through the ranks,” says Edwin Van Bommel, Chief Cognitive Officer at IPsoft.
In many ways, the shift to cognitive is much like a merger or acquisition — which are notoriously prone to failure. What may look good on paper rarely pans out when humans get involved, because we have all sorts of biases and preferences that don’t fit into neat little strategic boxes.
The one constant in the history of technology is that the future is always more human. So if you expect to cognitive applications simply to reduce labor, you will likely be disappointed. However, if you want to leverage and empower the capabilities of your organization, then the cognitive future may be very bright for you.
The Trump Administration said Wednesday that unspecified local and state agencies as well as tribal authorities would help the federal government to create a set of drone regulations for commercial flights.
The U.S. Department of Transportation and the Federal Aviation Administration, which oversee drones in the national airspace, released rules in Aug. 2016 for how businesses can use drones for tasks like aerial photography or to monitor farms. However, many states and local governments have enacted their own drone rules that in many cases conflict with current FAA regulations.
Although the FAA has approved some companies to use drones to photograph property damage, for example, doing so could potentially violate local privacy laws if drones take pictures of nearby homes without their owners’ consent.
This mishmash of local and federal drone rules in addition to the hurdles to businesses of obtaining FAA approval for commercial drone flights has caused some companies like Amazon amzn and Google goog to move their test flights to countries like United Kingdom and Australia where laws are more lax.
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The Trump Administration’s drone program is intended to make it easier for companies to test drones by having local authorities, tribal government, companies, and the federal government work together. It’s also designed to give businesses more flexibility to fly drones at night, beyond the sight of human operators, and over people’s heads—things that are currently banned without approval but important to making drone deliveries a reality.
“Overall this is a hugely important step forward,” said attorney Lisa Ellman, who helps run the drone advocacy group Commercial Drone Alliance. “The intent is to open up the skies to commercial drones. It will help us gather data to inform future rule making.”
Still, the Trump Administration revealed limited details about how the new drone program, planned for the next three years, would work. For example, the administration said in a statement, “Prospective local government participants should partner with the private sector to develop pilot proposals,” but it did not say how those partnerships would function.
The DOT said it would evaluate at least five applications in which local authorities and companies will jointly propose plans for potential drone projects in certain municipalities. But, the DOT did reveal how it is determining the appropriate projects or its criteria for how it is selecting participants, likely to be many considering it will include numerous local governments as well as companies with competing interests.
The department also did not say how much the federal program would cost, but it added that the cost would be revealed in the coming days.
Nevertheless, several organizations and companies that are interested in drones are pleased about the Trump Administration’s initiative.
“The beauty of this program is that the White House is allowing everyone from cities to states to tribal authorities to apply,” Greg McNeal, co-founder of drone startup AirMap told Fortune in an email. “States and cities will apply to open the airspace for operations that they’re most interested in, that are the best fit for local conditions and complexities, and that allow them to welcome drone operations that can kickstart their drone economy.”
Drone advocacy group Small UAV Coalition, which represents companies like Google’s parent, Alphabet, and Amazon, also commended the program.
“As the pilot program gets underway, the Coalition looks forward to continuing to work with Congress, the FAA, and all stakeholders to advance long-term FAA reauthorization legislation that will help ensure that the United States fully embraces the immense economic potential and consumer benefits of UAS [drones] technology in the near-term,” the group said in a statement.
But just because the new drone program debuted, doesn’t mean that local authorities, the federal government, and corporate interests won’t butt heads. States are still free to enact their own drone law regardless of Trump’s proposal.
Supporters of Trump’s plan like the Small UAV Coalition, the Association for Unmanned Vehicle Systems International, and the Academy of Model Aeronautics praised how the new drone program still designates the FAA as the ultimate authority over drones, trumping local governments. One reason these groups like this is because local laws often impede corporate interests especially surrounding privacy laws, thus limiting the ability of companies to launch commercial drone projects.
“We are encouraged that this new program appears to preserve the FAA’s authority over the nation’s airspace,” said Academy of Model Aeronautics spokesperson Chad Budreau.
About why it’s taken so long for such a framework to be developed, Ellman explained that’s just the way Washington D.C. politics works.
“I think when you’re dealing with any major federal government policy, there’s just a lot of ‘I’s’ to be dotted and ‘T’s’ to be crossed,” Ellman said.
There are many business degrees and classes you can take as an aspiring entrepreneur. However, not all of these courses will be able to teach you valuable lessons only an experienced business owner would know.
Owning a business isn’t easy. It takes a lot of different skills and experience to lead an entire team, meet deadlines and complete several day-to-day tasks.
Whether you’ve recently launched a business or are in the process of opening your own company, there are important lessons you need to know. It can take years, even decades to grasp an idea or strategy that can help you and your business grow.
Here are just a few lessons I’ve learned along the way:
1. Family comes first.
The first lesson is the importance of family. Yes, your business is your baby, but you have to prioritize the people you love.
When you’re at home, focus on relaxing with your family and spending quality time with them. Time can fly by when you have a million things going on at work.
Use your time with family to rest and make the most of every minute. Family time is precious because at the end of the day, they’ll always be there for you during the good and bad times.
2. The lows are rock-bottom lows.
Many entrepreneurs will go through rock bottom lows. Whether it’s losing your biggest client or struggling to put food on the table, your lows will force you out of your comfort zone and push you to your limits.
You may experience “make or break” moments. You must power through, no matter how difficult it is.
Over 20 years ago I failed miserably on the first business that I opened. I had clients and cash coming in, but I had to close the business. I didn’t understand cash flow, operating expense, budgeting, or any of the other numbers.
Understanding the language of business–including financial statements–is essential.
The great thing about these rock bottom lows is you can use these tough lessons to embrace the suck and become a wiser person. There’s always a light at the end of the tunnel.
3. The highs are extremely rewarding.
Just like you may experience rock bottom lows, you may also experience extreme highs. Winning a client, expanding your business or being able to afford your own jet are just a few of the many successes you may experience as a business owner.
I’ve been fortunate with my success. My business has expanded to include speaking, online training products, books, webinars, and conducting mastermind groups, all as a way to serve more clients and keep up with demand.
Celebrate the wins and take note of what got you to that point. Learning from your best experiences are just as important as learning from your worst.
4. Little victories can turn into major victories.
Have a new customer? Made a new friend at the networking event? Hired a sales coach? If so, that’s fantastic.
Small victories can go a very long way. You never know when new customers will tell all their friends and bring you a lot more business. The new friend you made at the convention may bring you more prospects than you ever dreamed of.
I’ll say it again: Celebrate the little victories. You don’t know what new opportunities they may bring.
5. Mentors are necessary.
Whether it’s an executive coach or a former boss, mentors are necessary for ultimate success. To reach your full potential you’ll need someone there to guide you on your path.
Owning a business isn’t easy. Having someone always available to give you advice and keep you accountable will give you the support you need to achieve your vision.
6. There’s no “9 to 5.”
Your office hours may be 9:00 a.m. to 5:00 p.m., but that won’t always be the case for entrepreneurs. You can certainly devote yourself to work strictly during these office hours but you can’t expect to not work outside that time.
Some clients may expect you to be available or be able to answer urgent questions at any given time. A crisis may erupt at 6:00 a.m. and you may have to jump on it. It’s important to balance your work and home life but as a business owner, you must understand the term “office hours” may not apply in some situations.
These are just a few of the many lessons I’ve learned throughout the years. Unfortunately, some lessons are best learned with experience but hopefully I’ve saved you some trouble while you work your way towards success.
Never give up if something becomes tough, just power through it, surround yourself with support and you’ll always end up learning and becoming a smarter business owner. Best of luck!
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