Technology Archives – Page 3 of 4

Automated Justice: The Role of Artificial Intelligence In The US Justice System

8 years ago By cumeadi

(Quick crash course on what artificial intelligence is for those who might need a refresher.)

According to this Hubspot article released a couple of weeks ago, here’s a list of jobs that they think will most likely be taken by artificial intelligence (AI) in the next few years.

Telemarketers
Bookkeeping Clerks
Compensation and Benefits Manager
Receptionist
Couriers
Proofreaders
Computer Support Specialists
Market Research Analysts
Advertising Salespeople
Retail Salespeople

Here’s a list of jobs I think AI will take in the next 10 years:

Wealth advisers
Lawyers
Pilot
Tax Auditor
Truck Driver
Taxi Drivers
Investment Banker
Doctors?
Computer Programmer
Musician

If we get to the point we can depend on AI to take care of our health, transportation, taxes, money, and entertainment, why not go all the way and allow AI to enter areas of public institutions like our justice system? I thought I wouldn’t find much research on AI in the judicial system. It would be the one place AI dare not touch. Wrong.

Here’s an expert of an article from the Guardian. I’ts about 9 months old.

The AI “judge” has reached the same verdicts as judges at the European court of human rights in almost four in five cases involving torture, degrading treatment and privacy.

The algorithm examined English language data sets for 584 cases relating to torture and degrading treatment, fair trials and privacy. In each case, the software analysed the information and made its own judicial decision. In 79% of those assessed, the AI verdict was the same as the one delivered by the court.

The article goes on to say:

Dr Nikolaos Aletras, the lead researcher from UCL’s department of computer science, said: “We don’t see AI replacing judges or lawyers, but we think they’d find it useful for rapidly identifying patterns in cases that lead to certain outcomes.

“It could also be a valuable tool for highlighting which cases are most likely to be violations of the European convention on human rights.” An equal number of “violation” and “non-violation” cases were chosen for the study.

So it’s happening. There are people thinking, researching, and applying AI to judicial processes. Based on this particular simulation, its not that far off either. At 79% of verdicts in alignment with human judge verdicts, it will only get better and most likely serve as a qualifier/screening tool for cases that should be evaluated by human rights judges.

Dr. Aletras’ work seems very academic and more research focused with limited impact on the day to day European Human Rights Courts. Maybe in the future, they’ll be some application but not today. That may be the case for AI as a judge but how about other parts of the judicial system?

Then, I came upon this article in the New York Times that discusses how AI already plays a significant role in the judicial process. It’s a couple weeks old. AI systems are used from everything to evaluating evidence like DNA and fingerprints, to deploying police officers in the most efficient manner. Here’s a quick story from one of the applications that shows one of the key challenges:

“Take the case of Glenn Rodriguez. An inmate at Eastern Correctional Facility in upstate New York, MR. Rodriguez was denied parole last year despite having a nearly perfect record of rehabilitation . The reason? A high score from a computer system called Compas. The company that makes Compas considers the weighting of inputs to be proprietary information. That force Mr. Rodriguez to rely on his own ingenuity to figure out what had gone wrong.

This year, Mr. Rodriguez returned to the parole board with the same faulty Compas score He had identified an error in one of the inputs for his Compas assessment. But without knowing the input weights, he was unable to explain the effect of his error, or persuade anyone to correct it. Instead of challenging the result, he was left to try to argue for parole despite the result. “

Did Mr. Rodriguez deserve parole? Based on traditional parole metrics, yes. He has near perfect record of rehabilitation. Based on Compas, a private company that essentially tries to predict likelihood of recidivism based on “proprietary data” and “algorithms”, Mr. Rodriguez stood a higher than usual chance of coming back to jail and thought it would just make more sense to keep him there. Have you spotted the problem yet?

Back in the day, when I aspired to play point guard in the NBA, I would focus on shooting a ton of free throws. I thought if I could just get a high volume of free throws, I could increase my percentage. I was missing a ton of free throws and it didn’t look like shooting more was helping. It wasn’t until my eighth grade coach told me, ” Practice doesn’t make perfect, perfect practice makes perfect.” I can shoot all I want but if I have garbage form, I’m just practicing garbage form and wasting my time. As most of you know, my basketball career ended in retirement in eighth grade, but that lesson has stayed with me and has ample significance to AI and machine learning.

In order to improve AI and machine learning algorithms, they must be trained by real data. Specifically in the justice system, companies will work with the state and federal government to train and develop all types of algorithms. The problem is these systems often compound societal and institutional realities they are supposed used to prevent. They may be trained with a high volume of data, but its just like me shooting with bad form.

Remember Mr. Rodriguez? Lets take a look at ProPublica’s evaluation of Compas’s Recidivism Algorithm to see if we can see if there are any insights into Compas’s performance.(Give it a read if you have a chance) Here’s the summary of their analysis:

“Our (ProPublica) analysis found that:

Black defendants were often predicted to be at a higher risk of recidivism than they actually were. Our analysis found that black defendants who did not recidivate over a two-year period were nearly twice as likely to be misclassified as higher risk compared to their white counterparts (45 percent vs. 23 percent).

White defendants were often predicted to be less risky than they were. Our analysis found that white defendants who re-offended within the next two years were mistakenly labeled low risk almost twice as often as black re-offenders (48 percent vs. 28 percent).

The analysis also showed that even when controlling for prior crimes, future recidivism, age, and gender, black defendants were 45 percent more likely to be assigned higher risk scores than white defendants.

Black defendants were also twice as likely as white defendants to be misclassified as being a higher risk of violent recidivism. And white violent recidivists were 63 percent more likely to have been misclassified as a low risk of violent recidivism, compared with black violent recidivists.

The violent recidivism analysis also showed that even when controlling for prior crimes, future recidivism, age, and gender, black defendants were 77 percent more likely to be assigned higher risk scores than white defendants.”

How interesting, the analysis from ProPublica looks like it mimics some of the realities we see in our justice system. This shouldn’t be surprising, the Compas algorithm was most likely trained using data from states that most likely have laws, procedures, convictions, and outcomes in place that disproportionately affects males, and people of color and people in urban areas. It most likely has data points from over-policed areas.

When we leverage AI and machine learning, for any industry, we have to make sure we don’t allow the flaws in our institutions to creep into the systems we develop. If we do, the solutions are causing more harm than good.

-ProPublica published the calculations and data for this analysis on github

Hoarding 2.0

8 years ago By cumeadi

I have a problem. I’m a digital Hoarder. What does even that mean? Let me try and break it down for you.

I have multiple memory sticks, external hard drives, and cloud storage. They are full of pictures, movies, other videos, music, documents, books, and other random files that I don’t feel like deleting.

I never delete my email anymore. I archive with the hope they’ll someday be useful. I’m one of those zero inbox folks but I feel like I’m cheating by archiving and not deleting.

I bookmark everything. My Chrome browser most likely has bookmarks all the way back from December 2008. If I see something that want to go back to and I want to remember, I’ll automatically save as a bookmark. Just briefly looking through…. I’ve bookmarked craigslist post that no longer exist, reference pages for hobbies, jobs, and personal projects.

I haven’t even gotten to the two most notorious apps for hoarding behavior. Evernote and Pocket allow me to take still shots of the internet (literally and figuratively speaking.). I’ve used the evernote clipping tool extension to capture posts, images, and quotes I’ll most likely never look at again. I use to go pocket crazy. I’d save an article to pocket with the hope of reading it again but pocketing the article made it more likely I wasn’t going to read it.

I archive all my texts. I rarely delete call logs. I could go on and on.

I would understand if I had similar tendencies offline. Far from it. I keep my physical possessions to a minimum. My minimalist mindset doesn’t translate to my online existence.

How would I even go correcting my behavior? Is it something which needs to be corrected?

product · startups · Technology · Why?

Design Thinking in the Nigerian Context

9 years ago By cumeadi

It’s 2 AM and the electricity goes out. Annoyed, you walk outside to turn the generator on. In the process of turning the generator on, you realize there’s no gas in the gen. In the pitch black of night, its not difficult to see the large red canister of gas a couple of steps away. You get the canister and start to attempt to fill the gen. You realize there’s too much gas in the canister and its difficult to control the amount that goes into the gen so you start to think… You go into the kitchen and get a used plastic bottle, cut it in half and now you’ve created a funnel and cup. You head back outside, put the makeshift funnel on the gen and begin to fill the cup with gas and pour it in the funnel. You fill the tank, turn the gen on, and go back to sleep.

That story is design thinking in action. I’d argue with anyone that design thinking is not a process that Nigerians are foreign to. In fact, it’s been at the ethos at most grassroots solutions. There are so many small inventions and quick fixes that I see everyday. Why don’t you see some of these solutions in the market? I believe the challenges are threefold:

How do you get people to see their solution as valuable outside themselves?
How do you provide the platform for people to producttize/ commercialize their already working prototypes?
How do you protect ideas and create incentives for people to continue to create?

How do you get people to see their solution as valuable outside themselves?

This is consequence of innovating to live vs innovating to thrive. People are brilliant problem solvers in developing markets because they have to in order to survive. Design thinking concepts tend to become a framework that most people operate in without knowing it. The challenge is being able to think beyond the problem, which is challenging for the problem solvers. I would suggest getting up to the balcony like in this story below:

Let’s say you are dancing in a big ballroom. . . . Most of your attention focuses on your dance partner, and you reserve whatever is left to make sure you don’t collide with dancers close by. . . . When someone asks you later about the dance, you exclaim, “The band played great, and the place surged with dancers.”

But, if you had gone up to the balcony and looked down on the dance floor, you might have seen a very different picture. You would have noticed all sorts of patterns. . . you might have noticed that when slow music played, only some people danced; when the tempo increased, others stepped onto the floor; and some people never seemed to dance at all. . . . the dancers all clustered at one end of the floor, as far away from the band as possible. . . . You might have reported that participation was sporadic, the band played too loud, and you only danced to fast music.

. . .The only way you can gain both a clearer view of reality and some perspective on the bigger picture is by distancing yourself from the fray. . . .

If you want to affect what is happening, you must return to the dance floor.*-Ronald Heifetz

That often the most challenging place for problem solvers to get to but is central to seeing the value in an idea or a new process.

How do you provide the platform for people to producttize/ commercialize their already working prototypes?

This a more systemic and structural problem. With a lack of manufacturing and capital in developing markets, it’s often impossible to scale a new idea. I believe the improvement of technologies like 3D printing hold a tremendous opportunity to decrease the cost and increase the accessibility of manufacturing to the masses.

How do you protect ideas and create incentives for people to continue to create?

This is an interesting challenge that all countries face now. How do you protect people who create, while encouraging the free exchange of ideas so people can build upon them? Legal spaces like IP and copyright may not be as developed in a place like Nigeria but it presents a great opportunity to re-imagine what IP/Copyright law can look like in the information sharing age.

Politics · product · Technology · Why?

Kobayashi and the Leader of the Free World

9 years ago By cumeadi

***Disclaimer…. I’m a huge Star Trek fan. I’ve tried to simplify a little bit so you don’t have to know as much about Star Trek to understand what I’m trying to say.***

Kobayashi Maru is a star fleet training exercise that is used to evaluate a commander’s character and fortitude. The simulation in the Star Trek universe allows the cadet to command a federation star ship, and sends them to aid another Federation vessel, the Kobayashi Maru. The disabled ship is adrift in the Klingon neutral zone, and the ship commanded by the cadet entering the zone will be in violation of a treaty and liable to attack.

The cadet has to decide whether to rescue the stranded ship, creating an opportunity for an all-out war with the Klingons and jeopardizing his or her own vessel and crew-mates’ lives in the process, or leave the Kobayashi Maru to eventual destruction. If the cadet attempts to save the vessel, the simulation is programmed to guarantee that his or her own ship will be destroyed. Not only will he be unsuccessful in saving the Kobayashi Maru, but everyone else will die as well.

The object is to test the cadet’s character and presence of mind in the face of large-scale disaster and certain death. The creation of the Kobayashi Maru isn’t discussed as much in Star Trek cannon, although in the most recent reboot, it’s shown that Spock was the preliminary designer of the test. His Vulcan sense of logic proved to be very helpful in constructing the no win scenario.

When deciding on leaders, humans traditionally follow our gut and how we feel about a person. The mental models an heuristics used to make snap decisions on who to follow are legacy from our early days when we had to be very cautious about who we were hunting and gathering with. We decide leaders based on what they say but even more on how we perceive them. Don’t believe me? Take a read about JFK VS Nixon here.

While we can never get rid of the human perspective, shouldn’t we be responsible for aiding better decisions in who should be leaders? We should have our own Kobayashi Maru that we use to vet leaders where we can objectively see their character and fortitude. To be more specific, the president of the United States should be put through more than just public opinion to become president. We have the history of the world and technology to create all possible and future scenarios to test a candidate’s decision making skills. It’s not a heavy lift at all. Here are the steps:

Recognize that we are currently incapable of making the best decisions without more information.
Develop a Kobayashi Maru equivalent that runs through a week of various possible scenarios (domestic disasters, economic collapse, political brinkmanship,etc).
Have the potential president pick their team.
Run the simulations… Evaluate the results.

The hardest step is 1. Everything else is super doable. Our armed forces train just like this. I don’t think its too much to ask a potential Commander in Chief to go through similar training and evaluation.

There’s a lot of responsibility involved with picking the next leader of the free world . Citizens should look at a Kobayashi Maru like exam as an opportunity to improve our decision making by exposing the decision making process of our future leaders in life- like situations.

Or we can just watch them play The Sims.

#productideas · business · product · startups · Technology

Disrupting VC

9 years ago By cumeadi

2 years ago, when tiphub was started, our core team had a couple of initial assumptions that came to be true.

Bootstrapping is important, however majority of disruptive technologies need early capital.
Venture capital is broken. With failure rates that would not be accepted in any other industry, most vc’s continue business as usual. The best ones have found ways to de-risk their investments by leveraging marketing strategies but its not a sustainable model for all vcs in a given ecosystem.
The decision making process for investment selections was purposefully arbitrary. It allows gate keepers to claim a higher power than a regular person at picking companies that have the best chance of success.
Lack of diversity in decision making leads to unequal representation and missed opportunities.

Now, to throw a wrench in it all, bring in the African perspective. Not enough vc activity, not enough opportunities to invest in, not enough capital, etc etc.

The major issue with the private market is that its supposed or destined to be the engine of growth for developed and developing countries alike. However, we don’t have the correct scale-able processes, or institutions in place to really push the needle of investment at scale. The two major problems are;

How do you assess risk in a way that is accurate?
How do you match risk, interest, and expertise to ensure optimal outcomes?

So early on in the inception of tiphub, the idea and the hope was that we would create a platform that would exactly what is missing in the vc community. A platform that could learn, overtime, the best investments for an investor based on different inputs. We called this project tracker.

2 years later, on the anniversary of tiphub, I can say we’ve gotten to the second phase of the tracker which is a platform that will bring together experts, investors, and startups to learn from interactions, and we’ll move on to phase three, where things will start to get really interesting.

Stay tuned as we build what we hope will be a game changing platform that will improve outcomes for all entrepreneurs and investors.